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Julia – Merging Simplicity and Power in Machine Learning

10 Jul 11:10
@SSobol77 SSobol77
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Release v1.0: Julia – Merging Simplicity and Power in Machine Learning 🚀

Your gateway into the exciting world of machine learning - a rapidly growing field full of opportunities.

Welcome to the first release of our project!

This release provides a comprehensive guide showcasing the power of the Julia language for solving machine learning tasks – from data processing to deep learning.

The guide is divided into two main sections, presented as interactive Jupyter notebooks.


julia_ML


✨ What's in this release?

This release is split into two major parts, each focusing on a key library within the Julia ecosystem.

Part 1: DataFrames.jl Tutorial – Data Processing

This section consists of 6 (six) interactive notebooks designed to introduce you to the DataFrames.jl package. It focuses on solving specific problems to demonstrate how available functionalities can be applied to common data processing challenges.

Part 2: Flux.jl Tutorial – Deep Learning in Julia

This section is dedicated to Flux.jl, the primary deep learning library in Julia. You will learn:

  • Core components: Dense and Conv layers, activation functions (relu, σ), optimizers (ADAM, Descent), and loss functions (crossentropy).
  • Practical example: Building, training, and evaluating a neural network for MNIST image classification.
  • GPU acceleration: Instructions for speeding up computations using CUDA.jl.

🚀 How to Get Started?

To ensure that the notebooks work correctly, please follow these steps:

  1. Clone the entire repository: 
    git clone https://github.com/Cartesian-School/Julia-for-Machine-Learning.git
  2. Navigate to the directory where you downloaded the files.
  3. Launch Jupyter Notebook from this directory.
  4. Open the notebooks from the section you're interested in and start your journey into machine learning with Julia!

🔧 Versions and Compatibility

  • The DataFrames.jl section has been tested with Julia 1.11.3 and DataFrames.jl 1.7.0.
  • The Flux.jl section is compatible with the latest versions of Flux.jl and related packages.

You can check older commits and tags in this repository to find versions of the guide compatible with earlier package versions.

We hope this guide will be useful for the community. Thank you for your interest!


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