Tag: Machine

Machine Learning in a Non-Euclidean Space

What you will learn in this article. 1. There are different examples of non-Euclidean geometry, among them spherical geometry and hyperbolic geometry. 2. A hyperbolic space is a space of negative constant curvature. 3. There are different models of hyperbolic geometry, t...

How to use Huggingface to use LLama-2 on your custom machine?

Meta’s newly open-sourced LLama 2 Chat model has been making waves on the OpenLLMs Leaderboard. This powerful language model is now available for anyone, even commercially. Intrigued, I decided to try implementing LLama 2 myself. While the process was straightforward, it did require a few step...

Why you should start studying Quantum Machine Learning

Introduction Hello! Thank you for stopping by in my first of many posts on Medium. Here I intend to write and share posts about Quantum Machine Learning (QML). Why am I doing this and why Quantum ML? In the last few months I have been thinking about career and future and that many tools tha...

When AI Goes Astray: High-Profile Machine Learning Mishaps in the Real World

The transformative potential of artificial intelligence (AI) and machine learning has often made headlines in the news, with plenty of reports on its positive impact in diverse fields ranging from healthcare to finance. Yet, no technology is immune to missteps. While the success stories paint a p...

Updates on Hidden Markov Models in 2023 part7(Machine Learning)

Abstract : In the paper, we introduce the maximum entropy estimator based on 2-dimensional empirical distribution of the observation sequence of hidden Markov model , when the sample size is big: in that case computing the maximum likelihood estimator is too consuming in time by the classical Baum-W...

The Conformity Machine: How Social Media’s Panopticon Shapes Identity

My social feed looks nothing like my actual life. Perfectly filtered photos, witty anecdotes, political rants — this is the show we put on when we know we have an audience. But does the constant glow of the spotlight change the dance? Social media has placed us under constant surveillance, lik...

LangChain + Streamlit Llama : Bringing Conversational AI to Your Local Machine

In the past few months, Large Language Models (LLMs) have gained significant attention, capturing the interest of developers across the planet. These models have created exciting prospects, especially for developers working on chatbots, personal assistants, and content creation. The possib...

When AI Goes Astray: High-Profile Machine Learning Mishaps in the Real World

Why does PHP have a Machine Learning library?

Choosing the right tool for the job is key in programming. For example, JavaScript pairs well with Web Development, while Python is a great choice for Machine Learning. However, even if you are not familiar with the best programming language for your use case, a...

TOP 3 MACHINE LEARNING CERTIFICATIONS FOR AN INCREASED SALARY IN 2023

Bring your dream AI career to reality with the most sought-after AI certifications around the world. Enrol with the best credentials providers and earn big with every passing year. Machine Learning Certifications | USAII Digging into some core statistics, to begin with;...

Leveraging Clustering for Document Layout Analysis in Machine Learning Projects

Introduction In machine learning / AI projects, dealing with diverse document layouts can pose a significant challenge. However, by leveraging clustering techniques, we can identify documents with similar layouts and selectively augment the training data to improve model performance. In this blog...

Why does PHP have a Machine Learning library?

Free two Machine Courses from MIT IDSS

Are you curious about the amazing realm of machine learning? Imagine teaching computers to learn from data and make intelligent decisions — that’s what machine learning is all about! At the Institute for Data, Systems, and Society (IDSS) at MIT, you can dive into this exciting field thro...

Boosting Model Accuracy: Techniques I Learned During My Machine Learning Thesis at Spotify (+Code Snippets)

In 2021, I spent 8 months building a predictive model to measure user satisfaction as part of my Thesis at Spotify. Image by Author My goal was to understand what made users satisfied with their music experience. To do so, I built a LightGBM classifier whose output was a binary r...

LangChain + Streamlit+ Llama : Bringing Conversational AI to Your Local Machine

Parsnip: Where Machine Learning Models Snap Together Like LEGO Mindstorms

In the intricate landscape of machine learning, each algorithm and model is like a unique LEGO piece. They come in various shapes, sizes, and colors, each offering its own distinct function. Whether you’re working with the sturdy ‘brick’ of linear regression or the intricate &lsquo...

When AI Goes Astray: High-Profile Machine Learning Mishaps in the Real World

How far have we come with Wireless sensor networks part2(Machine Learning)

Abstract : Wireless sensor networks (WSNs) are self-organizing monitoring networks with a large number of randomly deployed microsensor nodes to collect various physical information to realize tasks such as intelligent perception, efficient control, and decision-making. However, WSN nodes are powere...

God-Level Data Science Machine Learning Full Stack Roadmap 2023

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Machine Learning Engineers — What Do They Actually Do?

The title is a trick question, of course. Much like Data Scientist before it, the title Machine Learning Engineer is developing into a trend in the job market for people in our profession, but there is no consensus about the meaning of the title or the functions and skills it should encompass. I ima...

How far have we come with Wireless sensor networks part2(Machine Learning)

Working with Mutual Information Estimation part8(Machine Learning)

Abstract : Channel capacity plays a crucial role in the development of modern communication systems as it represents the maximum rate at which information can be reliably transmitted over a communication channel. Nevertheless, for the majority of channels, finding a closed-form capacity expression r...

How Brunn-Minkowski inequality is used in Machine Learning part2

Abstract : The present paper investigates the sub-Riemannian version of the equivalence between the curvature-dimension conditions and strong Brunn-Minkowski inequalities in the sub-Riemannian Heisenberg group Hn. We adopt the optimal transport and approximation of Hn developed by Ambrosio and Rigot...

Mastering Monte Carlo: How to Simulate Your Way to Better Machine Learning Models

How a Scientist Playing Cards Forever Changed the Game of Statistics In the tumultuous year of 1945, as the world was gripped by what would be the final throes of World War II, a game of solitaire quietly sparked an advancement in the realm of computation. This was no ordinary game, mind you, but...

Working with Delaunay Complex part3(Machine Learning)

Abstract : We give sufficient conditions for a discrete set of points in any dimensional real hyperbolic space to have positive anchored expansion. The first condition is a bounded mean density property, ensuring not too many points can accumulate in large regions. The second is a bounded mean vacan...

Working with Delaunay Complex part2(Machine Learning)

Abstract : Computing Delaunay triangulations in Rd involves evaluating the so-called in\_sphere predicate that determines if a point x lies inside, on or outside the sphere circumscribing d+1 points p0,…,pd. This predicate reduces to evaluating the sign of a multivariate polynomial of degree ...

Mastering Design Principles for Machine Learning

Software design principles are general guides for developing clean, readable and maintainable code. Design principles are important because they provide best practices that help ensure that code can be easily understood, reused, scaled and tested. Writing code without incorporating at least some of ...

Machine Learning’s Public Perception Problem

I was listening to a podcast recently with an assortment of intelligent, thoughtful laypeople (whose names I will not share, to be polite) talking about how AI can be used in healthcare. I had misgivings already, because they were using the term “AI”, which I find frequently means everyt...

First Step in Demystifying the Support Vector Machine (SVM): Learning and Implementing the Maximal Margin Classifier (MMC)

Suppose we have a binary classification problem and presumably the data is linearly separable, we can define an infinite number of hyperplanes that distinctively separates them. But, how do we pick the optimal hyperplane? A peregrine falcon resting on top a tree branch. Photo by Delaney ...

Free From Limitations: The Validation of Machine Hallucinations at MoMA

Since 1929, the Museum of Modern Art (MoMA) in New York City has served as an art lover’s mecca. It’s a lighthouse that shines a light on avant-garde paintings and sculptures, and since the definition of “modern art” is continually in flux, its collections are, too. Now, this...

Monitoring Machine Learning Models in Production: Why and How?

Machine Learning (ML) model development often takes time and requires technical expertise. As data science enthusiasts, when we acquire a dataset to explore and analyze, we eagerly train and validate it using diverse state-of-the-art models or employing data-centric strategies. It fee...

How I Deployed a Machine Learning Model for the First Time

Introduction For as long as I’ve started with machine learning, Jupyter Notebooks have been my most loyal sidekick. From data preprocessing to model training, fine-tuning, and testing, Jupyter Notebooks have been there at every step to support me. However, I always knew that there is an ent...

Machine Learning in Your Browser

If you’re working in IT, you have said the magic seven letters ChatGPT at least once in the last few months and you’ll probably remember at least one news story revolving around AI. It’s probably the hype topic of the century. Today, I want to show you an often overlooked aspect. ...

Building Real-time Machine Learning Foundations at Lyft

In early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving, training, CI/CD, feature serving, and model monitoring systems. On the real-time front, LyftLearn supported real-time inference and input feature validati...

Machine Learning Engineers — What Do They Actually Do?

Machine Learning Interview Questions 2023

As per my recent Interview experience I have created a list of questions on various Machine Learning Sections. This list will comprise of just questions, I am planning to write a separate blog post for all the answers. Machine Learning Interview Questions What is Regression? What are ...

Mastering Monte Carlo: How to Simulate Your Way to Better Machine Learning Models

Machine Learning with Expert Models: A Primer

Expert models are one of the most useful inventions in Machine Learning, yet they hardly receive as much attention as they deserve. In fact, expert modeling does not only allow us to train neural networks that are “outrageously large” (more on that later), they also allow us to build mod...

Automated Feature Selection for Machine Learning in Python

Feature selection is the process of identifying the most important and informative features within a dataset. It is one of the most important steps of machine learning modeling pipeline, since it has significant impact on model performance and its predictive power. Simple Visualization of Fea...

God-Level Data Science Machine Learning Full Stack Roadmap 2023

How You Should Validate Machine Learning Models

Large language models have already transformed the data science industry in a major way. One of the biggest advantages is the fact that for most applications, they can be used as is — we don’t have to train them ourselves. This requires us to reexamine some of the common assumptions abou...

Machine Learning in a Non-Euclidean Space

Machine Learning Made Intuitive

What is Machine Learning? Sure, the actual theory behind models like ChatGPT is admittedly very difficult, but the underlying intuition behind Machine Learning (ML) is, well, intuitive! So, what is ML? Machine Learning allows computers to learn using data. But what does this mean? How d...

10 Most Common Machine Learning Algorithms Explained -2023

1. Linear Regression Linear regression is a statistical method used to examine the relationship between two continuous variables: one independent variable and one dependent variable. The goal of linear regression is to find the best-fitting line through a set of data points, which can then be use...

Best Research of Arborescences part2(Machine Learning + Graph Theory)

Abstract : An arborescence, which is a directed analogue of a spanning tree in an undirected graph, is one of the most fundamental combinatorial objects in a digraph. In this paper, we study arborescences in digraphs from the viewpoint of combinatorial reconfiguration, which is the field where we st...

Building Real-time Machine Learning Foundations at Lyft

Mastering Design Principles for Machine Learning

Building a Trading Strategy with Machine Learning Models and Yahoo Finance in Python.

Developing a successful trading strategy requires a combination of market knowledge, technical analysis, and the ability to leverage data effectively. Machine learning models, coupled with financial data from sources like Yahoo Finance, offer a powerful approach to building robust trading strategies...

Machine Learning’s Public Perception Problem

How to Design a Roadmap for a Machine Learning Project

What is the first thing you do when starting a new machine learning project? I’ve posed this question to a variety of ML leaders in startups and have received a few different answers. In no particular order: Try out one of our existing models to see if it works for the new task. Sta...

Machine Learning — Vector Database: COMPARE and UNDERSTAND

In today’s digital age, databases are the cornerstone of nearly every application, from email clients to complex Enterprise Resource Planning (ERP) systems. Traditional database architectures like SQL, NoSQL, and Graph databases have their merits, but what about applications that need to simul...

Inside GPT — I : Understanding the text generation

Regularly engaging with colleagues across diverse domains, I enjoy the challenge of conveying machine learning concepts to people who have little to no background in data science. Here, I attempt to explain how GPT is wired in simple terms, only this time in written form. Behind ChatGPT’s p...

Machine Learning with Expert Models: A Primer

Machine Learning Platform at Walmart

Abstract Walmart is the world’s largest retailer, and it handles a huge volume of products, distribution, and transactions through its physical stores and online stores. Walmart has a highly optimized supply chain that runs at scale to offer its customers shopping at lowest price. In the pr...

Streamlining Machine Learning with the caret Package in R

In the rapidly evolving world of data science and machine learning, efficiency and simplicity are paramount. Developers and data scientists often seek tools that can streamline complex tasks, enabling them to focus on the core aspects of their projects. One such tool in the realm of R programming is...

A Roadmap to Become a Machine Learning Engineer

As a Machine Learning Engineer, I remember feeling uncertain about the path ahead when I first started out. Back then, I had no idea that the title “Machine Learning Engineer” even existed when I was working on my Text-to-Speech study for my Bachelor’s thesis. But it has become a p...

How I Deployed a Machine Learning Model for the First Time

For as long as I’ve started with machine learning, Jupyter Notebooks have been my most loyal sidekick. From data preprocessing to model training, fine-tuning, and testing, Jupyter Notebooks have been there at every step to support me. However, I always knew that there is an entire world beyond...

Machine Learning Engineers — what do they actually do?

Lessons Learned while doing Machine Learning at scale using Python and Google Cloud.

I recently worked on a number of projects for implementing machine learning pipelines at scale while optimizing them to save costs. Here are my titbits to make your ML projects time and cost-efficient. 1. Perform Feature Generation in the Database Query itself. This is probably the biggest and...

Machine Learning: Understand Centering and Scaling purposes

This article introduces the centering and scaling concepts. With a real-world use case, I explain the advantages of the center and scale the data. We dive into simple calculations and explanations by looking at Scikit-Learn ready-made methods. Technically, we compare the MinMaxScaler, Standar...

Research based on Metric Measure Spaces in Machine Learning part4

Assume that (X,d,μ) is a metric space endowed with a non-negative Borel measure μ satisfying the doubling condition and the additional condition that μ(B(x,r))≳rn for any x∈X,r>0 and some n≥1. Let L be a non-negative self-adjoint operator on L2(X,μ). We assume that e−t...

Churn Prediction With Machine Learning

A complete work in data science, through exploratory analysis, feature engineering techniques, model selection and model creation of predictive machine learning and hyperparameter tuning. Photo by Markus Winkler on Unsplash Churn rate, also known as customer attrition or cus...

Mastering Monte Carlo: How To Simulate Your Way to Better Machine Learning Models

In the tumultuous year of 1945, as the world was gripped by what would be the final throes of World War II, a game of solitaire quietly sparked an advancement in the realm of computation. This was no ordinary game, mind you, but one that would lead to the birth of the Monte Carlo method(1). The play...

Quick Midjourney Update: 4 key highlights to know

There was no Office Hours event on 30th August 2023. Here’s a quick rundown of the most recent Midjourney Weekly Office Hours in the first week of September: (1) Upcoming web releases There will be two release phases to ensure stability before introducing several new features. Th...

Advanced AI Training — Deep Intro to Graph Neural Nets GNN

eXacognition AI has released on their Youtube channel the next session video in the Deep Intro to AI Bootcamp series of introductory AI training presentations on advanced Artificial Intelligence design that I created & presented earlier this year to their client base. I personally perceive Gr...

Claw Machine Mini Game: Your Chance to Win Up to $5000 in BTCS!

Step into the exhilarating world of Bitcoin Spark’s Claw Machine Mini Game and prepare yourself for the opportunity of a lifetime. As an ICO participant, you now have the exclusive chance to take part in this thrilling game that offers incredible prizes, with a total value of up to $5000 in BT...

How Quasiconvexity works part7(Machine Learning)

We prove homogenization for a class of viscous Hamilton-Jacobi equations in the stationary and ergodic setting in one space dimension. Our assumptions include most notably the following: the Hamiltonian is of the form G(p)+βV(x,ω), the function G is coercive and strictly quasiconvex, minG...

Machine Learning in a Non-Euclidean Space

How Quasiconvexity works part8(Machine Learning)

We establish that for any non-empty, compact set K⊂R3×3sym the 1- and ∞-symmetric div-quasiconvex hulls K(1) and K(∞) coincide. This settles a conjecture in a recent work of Conti, Müller and Ortiz (Symmetric Div-Quasiconvexity and the Relaxation of Static Problems. Arch. ...

Forget PIP, Conda, and requirements.txt! Use Poetry Instead And Thank Me Later

Library A requires Python 3.6. Library B relies on Library A but needs Python 3.9, and Library C depends on Library B but requires the specific version of Library A that is compatible with Python 3.6. Welcome to dependency hell! Since native Python is rubbish without external packages for data...

Support Vector Machine- A beginner overview

Today’s topic is Support Vector Machines (SVM), a concept in Machine Learning widely used for tasks like image and text classification, as well as face detection. SVM falls under the category of Supervised Learning in Machine Learning. In Supervised Learning, we teach the computer to recognize...

Why Does All AI Art Look Like That?

Way back in the 1990s, I went to Art School. It was challenging, fun, and informative and among many of the memories I have from the time, one stands out with regard to the ongoing discussion about AI-generated art. Life Drawing was one of the first classes all first-semester students had to ...

Machine Learning Models for Sports Betting Unleashing the Power of Web Scraping with Selenium.

Sports betting has evolved into a sophisticated field where data-driven decisions can make the difference between success and failure. In this article, we will explore how to leverage web scraping with Selenium in Python to gather data from 1bets and then build machine learning models to enhance you...

How Quasiconvexity works part3 Machine Learning

We introduce a notion of convexity with respect to a one-dimensional operator and with this notion find a one-parameter family of different convexities that interpolates between classical convexity and quasiconvexity. We show that, for this interpolation family, the convex envelope of a continuous b...

How Quasiconvexity works part4(Machine Learning)

for a new class of costs c(x,y) for which we introduce a tentative notion of twist condition. In particular we study the conditions under which the infinitely-motonone minimizers are induced by a transportation map. We also state a uniqueness result for infinitely cyclically monotone Monge minimizer...

How Quasiconvexity works part1(Machine Learning)

Let X be a metric space and BCl(X) the collection of its bounded closed subsets as a metric space with respect to Hausdorff distance (and call BCl(X) the bounded-subset space of X). The question of whether or not one can characterize (the existence of) a rectifiable path in some subspace J of BCl(X)...

How to Crack Machine learning Interviews at FAANG!

Cracking a machine learning interview at companies like Facebook, Google, Netflix, Snap etc. really comes down to nailing few patterns that these companies look for. In this article, I plan to share my experience interviewing with these companies and also how I went about preparing. About me: ...

3 Types of Seasonality and How to Detect Them

  Seasonality is one of the key components that make up a time series. Seasonality refers to systematic movements that repeat over a given period with a similar intensity. Seasonal variations can be caused by various factors, such as weather, calendar, or economic conditions. Examples abo...

Why you should start studying Quantum Machine Learning

In the last few months I have been thinking about career and future and that many tools that I currently work with nowadays did not exist 10 years ago, and then I thought: how things are going to be in 10 years from now? Well, the most honest answer is I don’t know, but I can try and make a gu...

Mixed Effects Machine Learning with GPBoost for Grouped and Areal Spatial Econometric Data

The GPBoost algorithm extends linear mixed effects and Gaussian process models by replacing the linear fixed effects function with a non-parametric non-linear function modeled using tree-boosting. This article shows how the GPBoost algorithm implemented in the GPBoost library&nbs...

A Guide to Real-World Data Collection for Machine Learning

Whether you’re brand new to data science or the Chief Data Scientist at a large organization, you’ve probably played with perfectly crafted data sets to solve toy machine learning problems. Maybe you’ve used K-Means clustering to predict flower species in the Iris data se...

Making Machine Learning pipelines with Hausdorff Measure part4

In this paper we answer a question raised by David H. Fremlin about the Hausdorff measure of R2 with respect to a distance inducing the Euclidean topology. In particular we prove that the Hausdorff n-dimensional measure of Rn is never 0 when considering a distance inducing the Euclidean topology. Fi...

Building a Trading Strategy with Machine Learning Models and Yahoo Finance in Python.

Monte Carlo Approximation Methods: Which one should you choose and when?

  Since deterministic inference is often intractable with probabilistic models as we saw just now, we now turn to approximation methods based on numerical sampling, which are known as Monte Carlo techniques. The key question we will look at with these methods is computing the expec...

MLOPS and Azure Machine Learning Service

As a data engineer on Azure who works closely with data scientists and in data science projects, it’s my job to find and deploy the best tools for machine learning projects. Data science happens in notebooks, starts with a small idea and over the years has become more easy to use than ever bef...

Predicting NBA Salaries with Machine Learning

The NBA stands out as one of the most lucrative and competitive leagues in sports. In the last few years, the salaries of NBA players have been on an ascending trend, but behind every awe-inspiring dunk and three-pointer lies a complex web of factors that determine thes...

The Golden Age of Open Source in AI Is Coming to an End

I joined the Google Brain team in 2015 right as TensorFlow was open sourced. Contrary to popular belief, TensorFlow was not the secret sauce behind Google’s success at that point in time. Only a handful of researchers had used it, and it took several years before it transformed ...

Using Minkowski functionals in Machine Learning research

The study of the angular power spectrum of Cosmic Microwave Background (CMB) anisotropies, both in intensity and in polarisation, has led to the tightest constraints on cosmological parameters. However, this statistical quantity is not sensitive to any deviation from Gaussianity and statistical isot...

Adding Caccioppoli-type estimates in Machine Learning part1

We obtain Caccioppoli — type estimates for nontrivial and nonnegative solutions to the anticoercive partial differential inequalities of elliptic type involving degenerated p — Laplacian: $-Δ_{p,a} u:= -\mathrm{div}(a(x)|\na u|^{p-2}\na u)\ge b(x)Φ(u)$, where u is defined in a ...

How Banach space-valued functions are used in Machine Learning part3

We present a generalization of the Radon-Riesz property to sequences of continuous functions with values in uniformly convex and uniformly smooth Banach spaces. 2. On p-Dunford integrable functions with values in Banach spaces(arXiv)   Abstract : Let (Ω,Σ,μ) be a complet...

Can you learn machine learning in a year?

This post is for anyone considering a career move into the field of machine learning. Of course, the answer to the titular question is “it depends”. But what does it depend on, exactly? Rather than try and give some generic answer to the question that suits no one in particular, I ...

Machine Learning for Fraud Detection in Streaming Services

Streaming services serve content to millions of users all over the world. These services allow users to stream or download content across a broad category of devices including mobile phones, laptops, and televisions. However, some restrictions are in place, such as the number of active devices, the ...

10 Confusing XGBoost Hyperparameters and How to Tune Them Like a Pro in 2023

Today, I am going to show you how to squeeze XGBoost so hard that both ‘o’s pop out. We will achieve this by fine-tuning its hyperparameters to such an extent that it will no longer be able to bst after giving us all the performance it can. This will not be a mere hyperparam...

A Review of Propensity Score Modelling Approaches

In this article I’ll introduce the concept of a propensity score and what they’re used for before presenting 3 common methodologies. I’ll be discussing the following propensity score models: Propensity Score Matching with replacement (PSM) Propensity Score Matching w...

Structuring Your Machine Learning Project with MLOps in Mind

If you’re looking to take your machine learning projects to the next level, MLOps is an essential part of the process. In this article, we’ll provide you with a practical tutorial on how to structure your projects for MLOps, using the classic handwritten digit classification problem as a...

Deploy Machine Learning Models Right From Your Jupyter Notebook

Amidst this AI revolution, building intelligent systems at scale has been of great interest lately to countless organizations. While plenty of time and energy is being actively spent in training large machine learning models, taking these models to production and maintaining them is a task of its...

Kaggle competition: Predicting Sale Price of Corporación Favorita using Machine Learning

Whether you are a beginner or a professional working in Data Science, do yourself a favor and take part occasionally in competitions that resonate with your interests. If you are interested in machine learning, text analysis, exploratory analysis and more, consider showcasing your skills, ideas. Thi...

Fake News Detector: Combating Misinformation with Machine Learning

In the age of the internet, information flows faster than ever before. News travels at the speed of light, transcending borders and barriers. Yet, amidst this whirlwind of connectivity, a troubling phenomenon has emerged — a shadowy underworld of fake news, misinformation, and sensationalism. ...

These 5 Tips Will Help You Learn Data Science When You Have No Motivation to Study

One day you’re all gung-ho, creating a study schedule to teach yourself data science, and the next you’re finding excuses as to why you don’t have the time to study today. We all know that there are only so many times you can wash the walls of your apartment, clean out your refrige...

Unlocking the Power of Quantum Machine Learning: A Beginner’s Guide

Imagine a world where the limitations of classical physics do not bind computers. Instead, they harness the mind-bending properties of quantum mechanics. A world where machines can process information and solve complex problems unimaginably. This is the world of Quantum Machine Learning. From fin...

How Quasiconformal mapping is used in Machine Learning part5

We define Hardy spaces Hp, 0<p<∞, for quasiconformal mappings on the Korányi unit ball B in the first Heisenberg group H1. Our definition is stated in terms of the Heisenberg polar coordinates introduced by Korányi and Reimann, and Balogh and Tyson. First, we prove the exis...

GPT-4: 8 Models in One ; The Secret is Out

The GPT4 model has been THE groundbreaking model so far, available to the general public either for free or through their commercial portal (for public beta use). It has worked wonders in igniting new project ideas and use-cases for many entrepreneurs but the secrecy about the number of parameters a...

Simplify Your Machine Learning Projects

Many businesses are eager to adopt machine learning to improve their products and services. However, many data scientists get too caught up in creating the perfect model and using state of the art techniques. By doing this, they forget the most important thing: delivering a functional minimum viable...

Value Your Password

Ever have trouble remembering all your pin numbers and passwords? Well, imagine if you were the guy that forgot the password to an account that held $220m? That's what has happened to a San Fransisco man who wrote the password of his bitcoin account on a piece of paper. Oh yeah - you ...

Stop wasting times to learn Machine Learning! Read this instead!

Welcome to Machine Learning Tutorial. In this tutorial, we will do basic Machine Learning operations, starting with loading Python’s built-in data set to build svm with Iris Dataset. Machine Learning — First steps -Image by Author At the end of the article, you will see the qui...

The problem with anthropomorphizing algorithms

More and more people are using generative algorithms for a growing number of tasks, whether for text or image generation. OpenAI’s decision to apply the classic Silicon Valley philosophy of “move fast and break things” to machine learning and bring to market an unfinished prod...

All Languages Are NOT Created (Tokenized) Equal

Large language models such as ChatGPT process and generate text sequences by first splitting the text into smaller units called tokens. In the image below, each colored block represents a unique token. Short or common words such as “you”, “say”, “loud”, and &...

The Art of Prompt Design: Prompt Boundaries and Token Healing

This (written jointly with Marco Tulio Ribeiro) is part 2 of a series on the art of prompt design (part 1 here), where we talk about controlling large language models (LLMs) with guidance. In this post, we’ll discuss how the greedy tokenization methods used by langu...

Graph Machine Learning @ ICML 2023

We presented GraphGPS about a year ago and it is pleasing to see many ICML papers building upon our framework and expanding GT capabilities even further. Exphormer by Shirzad, Velingker, Venkatachalam et al adds a missing piece of graph-motivated sparse attention to ...

Predicting Stock Prices with Machine Learning

In the world of finance, predicting stock prices has always been a challenge that captures the imagination of investors, researchers, and data scientists alike. The ability to anticipate future price movements could potentially lead to significant gains, but it’s no secret that the stock marke...

Dynamic Pricing using Machine Learning

Have you ever looked up a plane ticket, and decided to buy later, only to come back and see the price has gone up a few hundred dollars? Have you ever experienced the same with concerts, hotels, or games? Have you ever thought about why Uber ride costs vary day to day? All of the above i...

Machine Learning Introduction

Corpus is the collection of our whole data X based on which our model will calculate to give out some data Y. When our model gives out some output Y based on the data stored in corpus as X is called Machine Learning, where we generally teach our model to give some output based on a lot of data fe...

The AI Brillo Box: End of Art Redefined in the Machine Learning Era

Arthur C. Danto, the philosopher and art critic celebrated for his avant-garde thought, ushered in a new perspective on art, one that finds resonance in the era of generative AI art. His redefinition of art, centered on collective acceptance rather than intrinsic aesthetic qualities, set the stage f...

This Company Uses Machine Learning to Track Your Antibodies

I’m writing this almost exactly three years after I first heard of the coronavirus. Although by now just about everyone I know has suffered a COVID-19 infection (or two), so far I’ve somehow escaped without so much as a sniffle. Am I off the hook? Or will I eventually succumb like everyo...

Dr. Andrew Ng’s Significant Contributions to Machine Learning

Dr. Andrew Ng is a name that resonates profoundly within the machine learning community. His work has been instrumental in shaping the trajectory of the field, and his influence is evident in both academic and industrial circles. Delving into the depth of his contributions, one can appreciate the ma...

Building an End-to-End Machine Learning Pipeline

You know, anyone can build a machine learning model these days. We’ve seen them springing up like mushrooms after the rain — predicting everything from stock prices to the next hit song on the radio. But today, we’re diving into something different, something that’s like the ...

MLOps: Bridging the Gap Between Machine Learning and Operations

In an era defined on innovation with a trends for data driven technologies, machine learning deployment into production ready to use interface become a worldwide business concern. In this landscape MLOps bridge the gap between ML lifecycle and deployment on devices ( web, mobiles, etc ) offering ...

How Bayesian Estimation works in different domains part2(Machine Learning)

In an earlier work, we demonstrated the effectiveness of Bayesian neural networks in estimating the missing line-of-sight velocities of Gaia stars, and published an accompanying catalogue of blind predictions for the line-of-sight velocities of stars in Gaia DR3. These were not merely point predicti...

XGBoost Algorithm in Machine Learning

XGBoost is a versatile machine learning algorithm that finds applications in a wide range of domains. Some of its common uses and applications: Classification: XGBoost is often employed for classification tasks, such as spam detection, image recognition, fraud detection, and sentiment analysis...

Graph Machine Learning

We presented GraphGPS about a year ago and it is pleasing to see many ICML papers building upon our framework and expanding GT capabilities even further.  Exphormer by Shirzad, Velingker, Venkatachalam et al adds a missing piece of graph-motivated sparse attenti...

What Does It Really Mean for an Algorithm to Learn?

When one first encounters machine learning, one often rushes through algorithm after algorithm, technique after technique, equation after equation. But it is afterwards that one can reflect on the general trends across the knowledge that they have acquired. What it means to ‘learn’ is...

Phoebe Bridgers Is My Own Personal Torture Machine

I am sad, numb, trying to hold on to things that once made me feel alive. And, as the Goo Goo Dolls dramatically sang, “you bleed just to know you’re alive.” Whenever I feel like emotions are a thing of the past and as though someone has scooped the Matilda out of me, that&rsquo...

Dry January (June): The Hunt for a More Efficient Running Machine

The fourth installment of a five-part series. For maximum enjoyment, please read the third installment before proceeding: Dry January (March): My Smartwatch Unleashed My 10,000-year-old Genes Part three: Ditching alcohol supercharged my battery, literally. medium.com Alcohol, my permanen...

Machine Dreams: Dean Blacc’s Subliminal Explanation of Color Theory

Dean Blacc’s attraction to abstraction and color is rooted in his organic and hands-on upbringing in the arts. A native Londoner, he spent much of his childhood perusing London’s art institutions and later in life he applied his learnings to design. He was both a practitioner and enabler...

Machine Learning is Fun! Part 2

Update: This article is part of a series. Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7 and Part 8! You can also read this article in Italiano, Español, Français, Türk&cc...

Databricks Machine Learning Associate Certification: A Comprehensive Study Guide

Progressing further into 2023, the global stage is being reshaped by the deep-seated effects of technology, specifically the tidal wave of artificial intelligence (AI) and ML. Databricks has positioned itself as the premier platform for training these advanced models, growing in popularity due to it...

Setting up my DEV-Machine

Usually I work on Unix based systems such as any Linux distribution or since a year now on a Mac. So the following steps will work on those machines out of the box. Some of the steps will work on Windows machines too. I am a developer with focus on backend and some DevOps, but from time to time s...

3 Tools that give you control of your Windows Machine

Windows is perhaps one of the most popular brand of Operating System out there. It is quite possible that your previous generation would have worked on Windows. It is also possible that you have had access to windows from an early age. You might also be familiar with the excitement that you might ha...

TryHackMe BLUE walkthrough — TryHackMe machine | by xer

Hey everyone!  Today, we’re diving into the thrilling world of hacking using TryHackMe’s Blue machine. If you’re new to this, don’t worry — we’ll take it step by step and keep it simple. Step 1: Scanning for Weak Spots  Use the following nmap scan ...

Hosting a website on Windows Virtual Machine

To host a website on windows virtual machine, we are required to install IIS (internet information service). The website will be available on the internet publicly as long as the machine is running. This situation can be avoided by using static IP addresses. In this article, we will only host a temp...

Buy Washing Machine Spare Parts in Delhi

If you’re looking for washing machine spare parts in Delhi, you’re in luck! We provide a wide range of spare parts that are both affordable and of top quality. Here’s why you should choose us as your supplier of washing machine spare parts in Delhi. Wide Range of Spare Part...

Flying to the Other Side

After a long wait upstairs for someone to push me, I breezed through security and passport control. I didn’t have to take anything out at all. No liquids or batteries or injections or laptop. Winning! All I had to remove was my hat to check my passport photo. As I expected, the plane passen...

Linda Jasmine is One Woman Entertainment Machine

Model and actress Linda Jasmine is a one-woman entertainment machine. She’s a former model who is also a social media influencer and reality TV star. Linda and her family starred on the Dutch reality TV show “Au Pairs,” which follows a group of Dutch au pairs and their adventure...

Photography as a time travel machine

What made me question this was a simple event in my life that happened on the streets of Prague. I was passing through one passageway of an old building in the center of the city. I noticed there was a photo exhibition of old photos from the end of the 19th and the beginning of the 20th century. The...

The Magic ATM Machine

I went to get cash from an ATM on Market Street in San Francisco. Two machines in the room; one being used and the other said “out of order”. While waiting for the good machine I observed a homeless-looking old man walking… slowly, painfully… down the other side of ...

What Is An Ice Cream Vending Machine

An ice cream vending machine is a type of vending machine that dispenses ice cream. Ice cream vending machines are typically found in public places such as parks, malls, and movie theaters. Ice cream vending machines come in a variety of shapes and sizes. Some ice cream vending machines...

Braving the Chill in Our Tangerine Machine

So, since autumn came round alarmingly fast — again — we were desperate to use what little sun we had forecast for one November weekend, and set off to Kingdom of Fife. The area of Fife is still commonly referred to as “kingdom” due to it actually having been an ancient Picti...

The Role of Machine Learning in Wildlife Conservation

Wildlife conservation is an essential undertaking that aims to preserve the diverse range of species and ecosystems found in nature, ensuring the protection of our planet. Conservationists have encountered increasingly difficult challenges over the years, primarily due to human activities, climate c...

The sorting machine: Exclusivity, striving, and how designers can (re)make style

If I had to guess, I’d say that Michael Sandel — political philosopher and Harvard professor — doesn’t care much about fashion. By that I don’t mean he dresses poorly. In fact, in his tie-less oxford shirt and sport coat, he cuts an affable figure of the academia a...

Welcome To Planet 325765-E, AKA The Beautiful Shit Machine

There’s something profoundly satisfying about emptying one’s rainbow colon into the chattering liquid, surrounded by luminous green fern and the mid-frequency hip hop of forest-dwelling Avifaunae. And one could argue that such a vivid experience might well be so infused with deli...

Women in Machine Learning: Negar Rostamzadeh

The recent debacle surrounding Google’s James Damore’s memo and subsequent firing illustrates that the source of gender imbalance in tech is still hotly disputed in certain quarters. But many organisations think it’s pretty clear that this gender imbalance stems from current s...

Machine Learning in Chemistry

the combination of machine learning and chemistry has made significant progress. Researchers are using advanced models like CNNs and RNNs for tasks such as creating new drugs, predicting toxicology, and modeling quantitative structure-activity relationships. The pursuit of models that are interpreta...

Extracting medicinal chemistry intuition via preference machine learning. Article review

The article ‘Extracting medicinal chemistry intuition via preference machine learning’ explores the innovative application of Artificial Intelligence (AI) in pharmaceutical chemistry. This research bridges the gap between traditional Drug Discovery methods and modern AI techniq...

Your Brain Is a Prediction Machine. What Does That Mean for Your Mental Health?

Predictive processing is an efficient way for the brain to handle information. Predicting helps filter and focus on important information, reducing the cognitive burden of processing everything in real-time. By anticipating likely outcomes and preparing appropriate responses, predictions allow us to...

Exploring scientific machine learning pipelines through the SimulAI toolkit

SciML, short for Scientific Machine Learning, encompasses work that merges quantitative sciences with machine learning. It has gained significant traction over the past decade, driven by the widespread availability of specialized hardware (such as GPUs and TPUs) and datasets. Additionally, it has be...

Exploring The Power of Causal Inference in Machine Learning

If you’re a data die-hard like me, who gets tired of the norm so easily, you must have started to ask yourself “what happens beyond relationship modeling. Machine Learning is good at predicting future outcome based on correlations in past data, but how do we go one step further?” ...

About Train, Validation and Test Sets in Machine Learning

This is aimed to be a short primer for anyone who needs to know the difference between the various dataset splits while training Machine Learning models. For this article, I would quote the base definitions from Jason Brownlee’s excellent article on the same topic, it is quite com...