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2. What to check about a Python machine learning book before ...

   www.aol.com/check-python-machine-learning-book...

   With so many books on Python machine learning, making a choice is becoming increasingly difficult. It would a disappointment to get halfway through a 700-page machine learning book to realize it ...

3. scikit-learn - Wikipedia

   en.wikipedia.org/wiki/Scikit-learn

   scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

4. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

5. List of programming languages for artificial intelligence

   en.wikipedia.org/wiki/List_of_programming...

   It is mostly used for numerical analysis, computational science, and machine learning. [6] C# can be used to develop high level machine learning models using Microsoft’s .NET suite. ML.NET was developed to aid integration with existing .NET projects, simplifying the process for existing software using the .NET platform.

6. François Chollet - Wikipedia

   en.wikipedia.org/wiki/François_Chollet

   Chollet is the author of Xception: Deep Learning with Depthwise Separable Convolutions, [9] which is among the top ten most cited papers in CVPR proceedings at more than 18,000 citations. [10] Chollet is the author of the book Deep Learning with Python, [11] which sold over 100,000 copies, and the co-author with Joseph J. Allaire of Deep ...

7. Google JAX - Wikipedia

   en.wikipedia.org/wiki/Google_JAX

   Google JAX is a machine learning framework for transforming numerical functions. [1] [2] [3] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).

8. Timeline of machine learning - Wikipedia

   en.wikipedia.org/wiki/Timeline_of_machine_learning

   Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.

9. List of datasets for machine-learning research - Wikipedia

   en.wikipedia.org/wiki/List_of_datasets_for...

   OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...