Machine Learning

Interpreting Coefficients in Linear Regression Models

Linear regression models are foundational in machine learning. Merely fitting a straight line and reading the coefficient tells a lot. But how do we extract and interpret the coefficients from these models to understand their impact on predicted outcomes? This post will demonstrate how one can interpret coefficients by exploring various scenarios. We’ll explore the analysis of a single numerical feature, examine the role of categorical variables, and unravel the complexities introduced when these features are combined. Through this exploration, […]

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Machine Learning

A Gentle Introduction to Bayesian Statistics

Image by Pexels (Photo by Balázs Utasi) Bayesian statistics constitute one of the not-so-conventional subareas within statistics, based on a particular vision of the concept of probabilities. This post introduces and unveils what bayesian statistics is and its differences from frequentist statistics, through a gentle and predominantly non-technical narrative that will awaken your curiosity about this fascinating topic. Introduction Statistics constitutes an invaluable set of methods and tools for analyzing and making decisions based on data. Their application in various […]

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Hardware and devices Leave a comment

What’s Your Story: Lex Story

GEHRKE: Welcome, Lex. LEX STORY: Oh, thank you. GEHRKE: Really great to have you here. Can you tell us a little bit about what you’re doing here at MSR (Microsoft Research) … STORY: OK. GEHRKE: … and how did you actually end up here? STORY: Well, um, within MSR, I actually work in the hardware prototype, hardware development. I find solutions for the researchers, especially in the areas of developing hardware through various fabrication and industrial-like methods. I’m a model […]

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Machine Learning

7 Machine Learning Projects That Can Add Value to Any Resume

Image by Author Learning by doing is the best way to master essential skills for becoming a machine learning engineer. Instead of just focusing on simple classification and regression models. In this blog, we will focus on advanced machine learning projects that will impact your resume and attract recruiters and hiring managers. We will learn about computer vision projects, speech recognition, stock price forecasting, fine-tuning Stable Diffusion and Llama 3, multi-step AI agent applications, and reinforcement learning. You will also […]

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Machine Learning

3 Ways of Using Gemma 2 Locally

Image by Author After the highly successful launch of Gemma 1, the Google team introduced an even more advanced model series called Gemma 2. This new family of Large Language Models (LLMs) includes models with 9 billion (9B) and 27 billion (27B) parameters. Gemma 2 offers higher performance and greater inference efficiency than its predecessor, with significant safety advancements built in. Both models outperform the Llama 3 and Gork 1 models. In this tutorial, we will learn about the three […]

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Python

Quiz: Primer on Jinja Templating

Interactive Quiz ⋅ 5 QuestionsBy Philipp Acsany Share In this quiz, you’ll test your understanding of Jinja templating. Jinja is a powerful tool for building rich templates in Python web applications, and it can also be used to create text files with programmatic content. The quiz contains 5 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score is 100%. Good […]

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Python

Exploring Astrophysics in Python With pandas and Matplotlib

This course uses three problems often covered in introductory astro-physics courses to play in Python. Along the way you’ll learn some astronomy, and how to use a variety of datascience libraries like NumPy, Matplotlib, pandas, and pint. In this video course you’ll learn about: Introductory astrophysics topics Working with dataframes in pandas Writing code that uses scientific units Visualizing information with Matplotlib What’s Included: Downloadable Resources:    

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Machine Learning

One Hot Encoding: Understanding the “Hot” in Data

Preparing categorical data correctly is a fundamental step in machine learning, particularly when using linear models. One Hot Encoding stands out as a key technique, enabling the transformation of categorical variables into a machine-understandable format. This post tells you why you cannot use a categorical variable directly and demonstrates the use One Hot Encoding in our search for identifying the most predictive categorical features for linear regression. Let’s get started. One Hot Encoding: Understanding the “Hot” in DataPhoto by sutirta […]

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Python

Quiz: The Walrus Operator: Python’s Assignment Expressions

Interactive Quiz ⋅ 8 QuestionsBy Geir Arne Hjelle Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of the Python Walrus Operator. This operator, used for assignment expressions, was introduced in Python 3.8 and can be used to assign values to variables as part of an expression. The quiz contains 8 questions and there is no time limit. You’ll get 1 point for each    

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Python

Quiz: Web Scraping With Scrapy and MongoDB

Interactive Quiz ⋅ 13 QuestionsBy Martin Breuss Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of Web Scraping with Scrapy and MongoDB. By working through this quiz, you’ll revisit how to set up a Scrapy project, build a functional web scraper, extract data from websites using selectors, store scraped data in a MongoDB database, and test and debug your Scrapy web scraper. The    

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