Python | Machine Learning | Coding

Forwarded from Data Science Machine Learning Data Analysis Books

#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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https://t.me/DataScienceM ✅

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Python | Machine Learning | Coding | R

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Python | Machine Learning | Coding | R

🔗 Machine Learning from Scratch by Danny Friedman

This book is for readers looking to learn new #machinelearning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different #algorithms create the models they do and the advantages and disadvantages of each one.

This book will be most helpful for those with practice in basic modeling. It does not review best practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.

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

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https://t.me/CodeProgrammer ✅

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Python | Machine Learning | Coding | R

Stanford’s Machine Learning - by Andrew Ng

A complete lecture notes of 227 pages. Available Free.

Download the notes:
cs229.stanford.edu/main_notes.pdf

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming #Keras

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Python | Machine Learning | Coding | R

"Machine Learning & LLMs for Beginners"

Don't miss these 2 books of 100-pages. Both are #FREE to read.

🌟 The Hundred-Page Machine Learning Book:
themlbook.com/wiki/doku.php

🌟 The Hundred-Page Language Model Book:
thelmbook.com

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https://t.me/CodeProgrammer 🌟

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Python | Machine Learning | Coding | R

Stanford's "Design and Analysis of Algorithms" Winter 2025

Lecture Notes & Slides: https://stanford-cs161.github.io/winter2025/lectures/

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming #Keras

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Python | Machine Learning | Coding | R

"Introduction to Probability for Data Science"

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

Download the book:
probability4datascience.com/download.html

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming #Keras

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Python | Machine Learning | Coding | R

📚

Become a professional data scientist with these 17 resources!

1️⃣ Python libraries for machine learning

◀️ Introducing the best Python tools and packages for building ML models.

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◀️ Learn deep learning concepts by combining text, math, code, and images.

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3️⃣ Anthology of Data Science Learning Resources

◀️ The best courses, books, and tools for learning data science.

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4️⃣ Implementing algorithms from scratch

◀️ Coding popular ML algorithms from scratch

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5️⃣ Machine Learning Interview Guide

◀️ Fully prepared for job interviews

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6️⃣ Real-world machine learning projects

◀️ Learning how to build and deploy models.

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7️⃣ Designing machine learning systems

◀️ How to design a scalable and stable ML system.

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◀️ Basic mathematical concepts necessary to understand machine learning.

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9️⃣ Introduction to Statistical Learning

◀️ Learn algorithms with practical examples.

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Machine learning with a probabilistic approach

◀️ Better understanding modeling and uncertainty with a statistical perspective.

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1️⃣ UBC Machine Learning

◀️ Deep understanding of machine learning concepts with conceptual teaching from one of the leading professors in the field of ML,

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1️⃣ Deep Learning with Andrew Ng

◀️ A strong start in the world of neural networks, CNNs and RNNs.

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Linear Algebra with 3Blue1Brown

◀️ Intuitive and visual teaching of linear algebra concepts.

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Machine Learning Course

◀️ A combination of theory and practical training to strengthen ML skills.

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Mathematical Optimization with Python

◀️ You will learn the basic concepts of optimization with Python code.

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Explainable models in machine learning

◀️ Making complex models understandable.

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Data Analysis with Python

◀️ Data analysis skills using Pandas and NumPy libraries.

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Python | Machine Learning | Coding | R

@Codeprogrammer Cheat Sheet Numpy.pdf

213.7 KB

This checklist covers the essentials of NumPy in one place, helping you:

- Create and initialize arrays
- Perform element-wise computations
- Stack and split arrays
- Apply linear algebra functions
- Efficiently index, slice, and manipulate arrays

…and much more!

Feel free to share if you found this useful, and let me know in the comments if I missed anything!

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Python | Machine Learning | Coding | R

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Loading CSV files into a database using Python.

#python #csv #dataAnalysis

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BEST DATA SCIENCE CHANNELS ON TELEGRAM

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Python | Machine Learning | Coding | R

from SQL to pandas.pdf

1.3 MB

🐼

"Comparison Between SQL and pandas" – A Handy Reference Guide

⚡️ As a data scientist, I often found myself switching back and forth between SQL and pandas during technical interviews. I was confident answering questions in SQL but sometimes struggled to translate the same logic into pandas – and vice versa.

🔸 To bridge this gap, I created a concise booklet in the form of a comparison table. It maps SQL queries directly to their equivalent pandas implementations, making it easy to understand and switch between both tools.

⚡ This reference guide has become an essential part of my interview prep. Before any interview, I quickly review it to ensure I’m ready to tackle data manipulation tasks using either SQL or pandas, depending on what’s required.

📕 Whether you're preparing for interviews or just want to solidify your understanding of both tools, this comparison guide is a great way to stay sharp and efficient.

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Python | Machine Learning | Coding | R

Numpy from basics to advanced.pdf

2.4 MB

📕

Mastering NumPy – From Basics to Advanced

NumPy is an essential library in the world of data science, widely recognized for its efficiency in numerical computations and data manipulation. This powerful tool simplifies complex operations with arrays, offering a faster and cleaner alternative to traditional Python lists and loops.

The "Mastering NumPy" booklet provides a comprehensive walkthrough—from array creation and indexing to mathematical/statistical operations and advanced topics like reshaping and stacking. All concepts are illustrated with clear, beginner-friendly examples, making it ideal for anyone aiming to boost their data handling skills.

#NumPy #Python #DataScience #MachineLearning #AI #BigData #DeepLearning #DataAnalysis

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Python | Machine Learning | Coding | R

Polars.pdf

391.5 KB

📖 A comprehensive cheat sheet for working with Polars

🌟 Have you ever worked with pandas and thought that was the fastest way? I thought the same thing until I worked with Polars.

✏️ This cheat sheet explains everything about Polars in a concise and simple way. Not just theory! But also a bunch of real examples, practical experience, and projects that will really help you in the real world.

┌ 🐻‍❄️ Polars Cheat Sheet
├ ♾️ Google Colab
└ 📖 Doc

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Python | Machine Learning | Coding | R

🥇 40+ Real and Free Data Science Projects

👨🏻‍💻 Real learning means implementing ideas and building prototypes. It's time to skip the repetitive training and get straight to real data science projects!

🔆 With the DataSimple.education website, you can access 40+ data science projects with Python completely free ! From data analysis and machine learning to deep learning and AI.

✏️ There are no beginner projects here; you work with real datasets. Each project is well thought out and guides you step by step. For example, you can build a stock forecasting model, analyze customer behavior, or even study the impact of major global events on your data.

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Python | Machine Learning | Coding | R

New to Pandas?

Here's a cheat sheet you can download (2025)

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