11 open-source projects similar to luispedro/buildingmachinelearningsystemswithpython, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best BuildingMachineLearningSystemsWithPython alternative.
This project is a C++ learning resource and study guide consisting of structured notes and programming examples. It provides practical implementations and exercise solutions covering core language syntax, data types, and control flow. The repository features specialized samples for object-oriented design, including class inheritance, polymorphism, and abstract classes. It includes demonstrations of memory management techniques such as dynamic allocation, move semantics, and placement new, as well as template programming examples for creating generic functions and data structures. The codebas
This project is a collection of TensorFlow machine learning examples providing reference implementations for various neural network paradigms. It covers supervised, unsupervised, reinforcement, and sequential learning models. The repository includes implementations for convolutional neural networks focused on image classification and ranking, as well as recurrent neural networks for time-series forecasting and sequence-to-sequence translation. It further provides examples of reinforcement learning agents trained via reward optimization and unsupervised learning techniques such as autoencoders
Learning scikit-learn: Machine Learning in Python.
Example code for the Wiley book "Machine Learning - Hands On for Developers and Technical Professionals"
Code from the book Machine Learning Systems.
Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.
This repository contains the code accompanying the work done in How Machine Learning Works by Mostafa Samir, Manning Publications. All the code is written with python.
Machine Learning in Action
This project is an educational resource providing practical code examples and implementations of machine learning algorithms using the Python language. It serves as a guide for constructing predictive pipelines, clustering models, and dimensionality reduction within the Scikit-Learn ecosystem. The repository includes comprehensive demonstrations for supervised and unsupervised learning, as well as detailed examples for implementing neural networks and deep architectures. It also provides practical guidance on exporting model parameters to JSON and wrapping trained models in web APIs for produ
This project is a Python-based educational framework designed to simulate reinforcement learning algorithms and environments. It serves as a platform for reproducing classic textbook examples, allowing users to study agent behavior, policy improvement, and the fundamental mechanics of decision-making in controlled settings. The library provides implementations for core reinforcement learning concepts, including temporal difference learning, Monte Carlo episode sampling, and tabular value function approximation. It enables the analysis of specific algorithmic behaviors, such as identifying and
This project is a machine learning education resource consisting of Python implementations of statistical learning models and data analysis examples from a core textbook. It serves as a statistical modeling library that provides the code necessary to implement linear regression, classification, and unsupervised learning techniques for academic data analysis. The repository is structured as a reference-driven implementation, with a directory layout that mirrors the chapter and section hierarchy of the associated academic publication. It includes a set of scripts and notebooks designed to gener