Search Results for "tutorials" - Page 4
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Showing 93 open source projects for "tutorials"
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Coursera Machine Learning
Coursera Machine Learning By Prof. Andrew Ng
CourseraMachineLearning is a personal collection of resources, notes, and programming exercises from Andrew Ng’s popular Machine Learning course on Coursera. It consolidates lecture references, programming tutorials, test cases, and supporting materials into one repository for easier review and practice. The project highlights fundamental machine learning concepts such as hypothesis functions, cost functions, gradient descent, bias-variance tradeoffs, and regression models. It also organizes week-by-week course schedules with links to exercises, lecture notes, and additional resources. ... -
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Azure Machine Learning Python SDK
Python notebooks with ML and deep learning examples
...The content spans a wide range of real-world tasks — from foundational quickstarts that teach users how to configure an Azure ML workspace and connect to compute resources, to advanced tutorials on using pipelines, automated machine learning, and dataset handling. Because it is designed to work with Azure Machine Learning compute instances, many notebooks can be executed directly in the cloud without additional setup, but they can also run locally with the appropriate SDK and packages installed. Each notebook includes code, narrative explanations, and example workflows that help users build reproducible machine learning solutions, which are key for operationalizing models in production. -
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Girls-In-AI
Free learning code series: Xiaobai's introduction to Python
...The repository includes Jupyter notebooks, tutorials, and exercises that guide learners through topics such as data processing, machine learning model development, and Kaggle competition practice. One of the primary goals of the project is to support inclusivity in technology by encouraging more women and newcomers to explore programming and AI development. -
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TensorFlow Docs
TensorFlow latest official documentation Chinese version
...Its goal is to make the extensive TensorFlow ecosystem more accessible to developers and researchers who prefer to learn in Chinese. The repository contains translated guides, API explanations, tutorials, and conceptual documentation that mirror the structure of the original TensorFlow documentation site. Contributors from technology companies, universities, and the open-source community collaborate to maintain and update the translations so they stay aligned with new TensorFlow releases. The documentation covers fundamental concepts such as tensors, computational graphs, model training, optimization, and neural network APIs, along with advanced topics including distributed training and production deployment. -
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MIT Deep Learning
Tutorials, assignments, and competitions for MIT Deep Learning
MIT Deep Learning is an open-source repository that contains tutorials, assignments, and learning materials related to deep learning courses taught at MIT. The repository provides hands-on tutorials that introduce the fundamental concepts behind neural networks, deep learning architectures, and modern machine learning techniques. Many of the tutorials include practical implementations that demonstrate tasks such as image classification, generative models, and neural network training workflows. ... -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. -
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Machine learning Resources
Some learning materials and research introduction on machine learning
Machine learning Resources is an educational GitHub repository that collects resources, tutorials, and implementation examples related to machine learning theory and practice. The project aims to help learners understand machine learning from both conceptual and practical perspectives by combining explanations, research references, and coding examples. It serves as a curated knowledge base that introduces fundamental algorithms and techniques used in modern machine learning systems. ... -
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stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course
This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1. -
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SSD Keras
A Keras port of single shot MultiBox detector
...The main goal of this project is to create an SSD implementation that is well documented for those who are interested in a low-level understanding of the model. The provided tutorials, documentation and detailed comments hopefully make it a bit easier to dig into the code and adapt or build upon the model than with most other implementations out there (Keras or otherwise) that provide little to no documentation and comments. Use one of the provided trained models for transfer learning. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Intel neon
Intel® Nervana™ reference deep learning framework
neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu... -
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AI-Blocks
A powerful and intuitive WYSIWYG to create Machine Learning models
A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models! The concept of AI-Blocs is to have a simple scene with draggable objects that have scripts attached to them. The model can be run directly on the editor or be exported to a standalone script that runs on Tensorflow. Variables are parsed from python scripts and can be edited from the AI-Blocs properties panel. To run your model simply press the "Play" button and let the magic happen! The project... -
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. ... -
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DeepLearningProject
An in-depth machine learning tutorial
This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. -
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Spark Python Notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis
Spark Python Notebooks is a curated collection of example Jupyter notebooks designed to help developers and data engineers learn Apache Spark using Python in an interactive environment. Rather than only providing static code files, this project uses notebooks to teach practical data processing workflows, exposing users to real Spark programming patterns like working with RDDs, DataFrames, and distributed computations. These notebooks often demonstrate how to transform, analyze, and visualize... -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn in tensorflow, and much more. Codes, theory, applications, and datasets about natural language processing, robotics, computer vision, and much more. -
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AlgoWiki
Repository which contains links and resources on different topics
AlgoWiki is an open educational repository that aggregates a large collection of curated resources covering many areas of computer science, programming, and algorithmic problem solving. The project functions as a structured knowledge index that links to tutorials, articles, courses, and research materials across numerous technical domains. Topics include algorithms, machine learning, artificial intelligence, programming languages, web development, and software engineering practices. The repository is organized into directories by subject so that users can easily locate relevant learning materials within a specific discipline. ... -
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Qix
Machine Learning, Deep Learning, PostgreSQL, Distributed System
...The project is designed as a curated index of useful tools, frameworks, research papers, and learning materials that developers can use to explore the AI ecosystem. It organizes information about libraries, tutorials, datasets, and software tools used in modern AI research and development. The repository helps developers quickly discover relevant technologies and educational resources without searching through multiple sources individually. It also includes references to frameworks, model implementations, and related research projects across various machine learning subfields. ...
