MACHINE LEARNING

Python Machine Learning By Example book with GitHub and 518 pages

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24 June 2026 7h42

Python Machine Learning By Example: http://
amzn.to/3MczBwk v/ @PacktDataML +
GitHub: https://
github.com/PacktPublishin
g/Python-Machine-Learning-By-Example-Third-Edition
… 518-pages! What you will learn: Machine learning best practices throughout data preparation and model development Build and improve image classifiers using

Machine Learning Solutions Architect Handbook: ML Lifecycle, MLOps, Generative AI

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24 June 2026 7h41

Machine Learning Solutions Architect Handbook — Practical Strategies and Best Practices in the ML Lifecycle, System Design, MLOps, and Generative AI: http://
amzn.to/4bx8t6b v/ @PacktDataML

Data Without Labels: Unsupervised Machine Learning Book Overview

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24 June 2026 7h30

Data Without Labels — Models and Algorithms for Practical Unsupervised Machine Learning: http://
amzn.to/4q5bbYz 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷: Fundamental building blocks and concepts of machine learning and unsupervised learning
Data cleaning for structured and

3rd Edition of Python Feature Engineering Cookbook for ML

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24 June 2026 7h29

3rd Edition! "Python Feature Engineering Cookbook", complete guidebook with recipes for crafting powerful features for Machine Learning models: http://
amzn.to/4rDWUT9 by @Soledad_Galli —————
#AI #ML #DataScience #DataScientist

Scikit-learn Cookbook 3rd Edition: 80+ Recipes, Preprocessing, Dimensionality

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24 June 2026 7h28

Scikit-learn Cookbook — 80+ recipes for Machine Learning in Python with scikit-learn [3rd Edition]: http://
amzn.to/4oDGOq7 v/ @PacktDataML 𝓒𝓸𝓷𝓽𝓮𝓷𝓽𝓼:
Common Conventions & API Elements of Scikit-Learn
Pre-Model Workflow and Data Preprocessing
Dimensionality

→ View original post on X — @pmddomingos

AI talent underpaid: each worth $150B as Google market cap fell 7%

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@pmddomingos

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24 June 2026 7h27

AI talent is still highly underpaid: Google’s market cap fell by 7% when Noam Shazeer and John Jumper left, so on average they’re each worth $150B .

AI Programming with Python: From Zero to Hero book overview

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24 June 2026 7h26

AI Programming with Python — From Zero to Hero: http://
amzn.to/43TkNea Thorough introductions to AI, Machine Learning, and Deep Learning Hands-on introductions to Python Discussions of supervised and unsupervised learning Explorations of classification and regression

XGBoost for Regression, Predictive Modeling, and Time Series Analysis

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24 June 2026 7h07

XGBoost for Regression, Predictive Modeling, and Time Series Analysis — Learn how to build, evaluate, & deploy predictive models: http://
amzn.to/4l2YcU9 v/ @PacktDataML

→ View original post on X — @jiqizhixin

SemanticQA: a new benchmark for evaluating LM comprehension

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@jiqizhixin

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24 June 2026 6h14

Do your language models truly grasp meaning, or are they just pretending? Researchers from Beijing University of Science and Technology and BIGAI present SemanticQA — a new benchmark that evaluates LMs' ability to handle expressions.