Machine Learning

Need a reference for algebra?

Here's a cheat sheet you can download

https://xn--r1a.website/DataScienceM

#Algebra #Statistics #Mathematics #DataAnalysis #Equations #Probability #MathSkills #NumbersGame #QuantitativeReasoning #MathIsFun

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4.7K viewsedited 12:19

Machine Learning

"Mathematical Foundations of Machine Learning"

PDF: https://nowak.ece.wisc.edu/MFML.pdf

#Mathematics #MachineLearning #AI #DataScience #MathFoundations #MLTheory #ArtificialIntelligence #EducationalResources #PDFResource #TechLearning

https://xn--r1a.website/DataScienceM

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4.91K viewsedited 12:22

Machine Learning

Forwarded from Machine Learning with Python

✅ Free ML Books You Should Know!

1⃣ Dive into Deep Learning: https://d2l.ai

🔢 Deep Learning: https://deeplearningbook.org

🔢 Interpretable Machine Learning: https://christophm.github.io/interpretable-ml-book/

🔢 Machine Learning Yearning: https://info.deeplearning.ai/machine-learning-yearning-book

🔢

Mathematics for Machine Learning: https://mml-book.github.io

🔢 An Introduction to Statistical Learning: https://statlearning.com

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Machine Learning

Forwarded from Machine Learning with Python

🗂

10 “Real Data Science Portfolio” Examples

1️⃣

Ken Jee Portfolio | Data Scientist

▶️

Field: Sports data analysis

👤

Link: Portfolio

2️⃣

Yassine Alouini's Portfolio | Kegel Master

▶️

Domain: Machine Learning and Kegel Competitions

👤

Link: Portfolio

3️⃣

Tatman Portfolio | Data Scientist

▶️

Domain: Natural Language Processing (NLP)

👤

Link: Portfolio

4️⃣

Robinson Portfolio | Data Scientist

▶️

Field: Statistical analysis and R programming

👤

Link: Portfolio

5️⃣

Siraj Raval's Portfolio | AI Instructor

▶️

Field: Machine Learning and Artificial Intelligence

👤

Link: Portfolio

6️⃣

Julia Silge's Portfolio | Data Scientist

▶️

Domain: Organized data and data visualization

👤

Link: Portfolio

7️⃣

Mueller Portfolio | Developer Scikit-Learn

▶️

Field: Machine learning and open source projects

👤

Link: Portfolio

8️⃣

Wickham Portfolio | Data Scientist

▶️

Area: R programming and data visualization

👤

Link: Portfolio

9️⃣

Portfolio of François Puget | Kegel Master

▶️

Domain: Advanced Machine Learning Techniques

👤

Link: Portfolio

🔟

Emily's Portfolio | Data Analyst at Disney

▶️

Domain: Data visualization and storytelling

👤

Link: Portfolio

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Machine Learning

Forwarded from Machine Learning with Python

Machine Learning Glossary

Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.

Link: https://ml-cheatsheet.readthedocs.io/en/latest/index.html

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4.91K views13:04

Machine Learning

Forwarded from Machine Learning with Python

1:09:25

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🔥

MIT has updated its famous course 6.S191: Introduction to Deep Learning.

.

All slides, #code and additional materials can be found at the link provided.

📌 Fresh lecture : https://youtu.be/alfdI7S6wCY?si=6682DD2LlFwmghew

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4.92K views02:31

Machine Learning

Forwarded from Machine Learning with Python

Numpy @CodeProgrammer.pdf

813.2 KB

🏳️‍🌈 "NumPy Library" Tutorial

👨🏻‍💻 For the past few days, I've been busy preparing this comprehensive tutorial on the NumPy library for data science, trying to cover all the tips and tricks of this library.

✅

Why is this booklet different? Because it is not written based on just theoretical concepts, but is the result of my own experiences and learning. It has real and practical examples that will help you better understand #NumPy concepts and use them in your projects.💯

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Machine Learning

👩‍💻 Prompt Engineering: A Practical Example

This real-world project tutorial covers zero-shot and few-shot prompting, delimiters, numbered steps, role prompts, chain-of-thought prompting, and more. Improve your LLM-assisted projects today.

Link: https://realpython.com/practical-prompt-engineering/

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5.33K viewsedited 11:12

Machine Learning

Forwarded from Machine Learning with Python

🔖 The book that paved the way for me to "data science"!

👨🏻‍💻 "Where do I start now?" This was the first and biggest question I faced when I started my Data Science learning journey!

⏪ I was really overwhelmed by the large number of scattered sources, long courses, and specialized books full of heavy terminology. I didn't know how to start and move forward in this direction...

✔️ But the book Intro to Data Science with Python changed everything for me and gave me a new perspective!

✏️ This book is a complete guide to starting from scratch and is great for both beginners and professionals in this field!! From coding with Python to working with data, visualization, and even AI tools, it explains everything in the simplest and most practical way possible.

💸 A great start for anyone looking to learn data science with Python!👇

┌ 🏳️‍🌈 Intro to Data Science with Python
├ 📄 E-book
└ 🐱 GitHub-Repos

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Machine Learning

Forwarded from Machine Learning with Python

course lecture on building Transformers from first principles:
https://www.dropbox.com/scl/fi/jhfgy8dnnvy5qq385tnms/lectureattentionneuralnetworks.pdf?rlkey=fddnkonsez76mf8bzider3hrv&dl=0

The #PyTorch notebooks also demonstrate how to implement #Transformers from scratch:
https://github.com/xbresson/CS52422025/tree/main/labslecture07

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5.01K views21:09

Machine Learning

Forwarded from Machine Learning with Python

Pandas Introduction to Advanced.pdf

854.8 KB

📄

"Pandas Introduction to Advanced" booklet

👨🏻‍💻 You can't attend a #datascience interview and not be asked about Pandas! But you don't have to memorize all its methods and functions! With this booklet, you'll learn everything you need.

✔️ One of the most useful and interesting combinations is using #Pandas with #AWS Lambda, which can be very useful in real projects.

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Machine Learning

Forwarded from Machine Learning with Python

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Machine Learning

Forwarded from Machine Learning with Python

Exercises in Machine Learning

This book contains 75+ exercises

Download, read, and practice:
arxiv.org/pdf/2206.13446

GitHub Repo: https://github.com/michaelgutmann/ml-pen-and-paper-exercises

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3.41K views01:00

Machine Learning

Forwarded from Machine Learning with Python

Linear Algebra

The 2nd best book on linear algebra with ~1000 practice problems. A MUST for AI & Machine Learning.

Completely FREE.

Download it: https://www.cs.ox.ac.uk/files/12921/book.pdf

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Machine Learning

#MachineLearning Systems — Principles and Practices of Engineering Artificially Intelligent Systems: https://mlsysbook.ai/

open-source textbook focuses on how to design and implement AI systems effectively

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9.92K viewsedited 06:47

Machine Learning

Forwarded from Machine Learning with Python

🔗 Machine Learning from Scratch by Danny Friedman

https://dafriedman97.github.io/mlbook/content/introduction.html

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3.87K views05:29

Machine Learning

Forwarded from Machine Learning with Python

"Introduction to Probability for Data Science"

One of the best books on #Probability. Available FREE.

Download the book:
probability4datascience.com/download.html

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Machine Learning

Mathematical theory of Deep Learning:

[Download 282-page PDF. Updated version]:
arxiv.org/abs/2407.18384

#AI #ML #MachineLearning #DeepLearning #Mathematics #DataScience #DataScientist

⚡️

BEST DATA SCIENCE CHANNELS ON TELEGRAM

🌟

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4.29K viewsedited 05:47

Machine Learning

Forwarded from Machine Learning with Python

Found an easy way to learn math for ML: Mathematics for Machine Learning 🎓📚

This is a curated collection on GitHub, including books, research papers, video lectures, and basic materials on math for studying and reviewing the mathematical foundations of machine learning. 📖📊

It helps build a stronger knowledge base by bringing together trusted resources around topics that machine learning engineers constantly encounter: linear algebra, mathematical analysis, probability theory, statistics, information theory, matrix calculus, and deep learning mathematics. 🧮🤖

Free public repository on GitHub. 💻✨

https://github.com/dair-ai/Mathematics-for-ML

#MachineLearning #Mathematics #DataScience #Learning #GitHub #AI

GitHub

GitHub - dair-ai/Mathematics-for-ML: 🧮 A collection of resources to learn mathematics for machine learning

🧮 A collection of resources to learn mathematics for machine learning - dair-ai/Mathematics-for-ML

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1.68K views16:52

Machine Learning

"Calculus: Early Transcendentals" is an excellent free textbook for building a solid foundation in mathematical analysis. 📘

The book is written in a clear and accessible language, while maintaining the necessary mathematical rigor. It contains a large number of examples and problems, making it suitable for both self-study and use in the educational process. 🎓

The textbook covers a wide range of topics, including:
• limits;
• derivatives;
• integrals;
• sequences and series;
• differential equations;
• multivariate analysis.

I consider this book another valuable tool in the arsenal of anyone studying mathematics. 🛠️

If you are a student and want to master or review key topics in mathematical analysis, or a teacher looking for new ideas and alternative explanations, this textbook is definitely worth attention.

https://open.umn.edu/opentextbooks/textbooks/415

https://github.com/antoniolupetti/algebrica

#Calculus #Math #FreeTextbook #StudyGuide #Mathematics #STEM

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