Handson-Mlp

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handson-mlp is an Open Source research & education tool that provides Jupyter notebooks for learning Machine Learning and Deep Learning. It uses Python with Scikit-Learn, PyTorch, and Hugging Face libraries.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is handson-mlp?

handson-mlp is an open-source project offering a series of Jupyter notebooks designed to teach the fundamentals of Machine Learning and Deep Learning in Python. It leverages popular libraries such as Scikit-Learn, PyTorch, and Hugging Face, providing practical examples and solutions to exercises. This resource is ideal for individuals looking to gain hands-on experience with ML and DL concepts, offering a structured learning path through various topics from basic machine learning landscapes to advanced transformers and reinforcement learning. Users can run these notebooks online via Colab or install them locally for a personalized learning environment.

Best used for

Ideal for students and teachers who need to learn machine learning fundamentals, practice deep learning techniques, and explore advanced AI models. Especially valuable for those seeking hands-on experience with Python, Scikit-Learn, PyTorch, and Hugging Face libraries.

Common actions

learn machine learning

practice deep learning

explore AI models

understand Python libraries

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Capabilities

Key features

Jupyter notebooks
Scikit-Learn integration
PyTorch integration
Hugging Face library support
Machine Learning fundamentals
Deep Learning concepts

Target Audience

studentteacher

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What programming languages and libraries are used in handson-mlp?

handson-mlp primarily uses Python and focuses on Machine Learning and Deep Learning concepts. It integrates with popular libraries such as Scikit-Learn, PyTorch, and Hugging Face, providing practical examples and exercises for these frameworks.

Can I run the handson-mlp notebooks online without installation?

Yes, you can run the handson-mlp notebooks online using platforms like Google Colab. This allows you to experiment with the code and concepts without needing to install anything on your local machine, though changes are temporary.

What topics are covered in the handson-mlp notebooks?

The notebooks cover a wide range of topics, including the machine learning landscape, classification, training linear models, decision trees, ensemble learning, dimensionality reduction, unsupervised learning, artificial neural networks, deep computer vision, NLP with RNNs and transformers, and reinforcement learning.

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