Welcome to MLlabs, a curated collection of lab assignments and tutorials designed to assist you in mastering various aspects of Machine Learning. This repository contains exercises and solutions ranging from image processing to building language models.
Here are the labs available in this repository:
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Lab Assignment: Introduction to Image Processing and Keras - Learn the basics of image processing techniques and how to use the Keras library for building models.
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Lab Assignment: Image Classification with Keras and CNNs - Understand how to build a Convolutional Neural Network (CNN) for image classification tasks using Keras.
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Lab: Building a Language Model with TensorFlow and Python - In this lab, learn how to build a language model using the TensorFlow library and Python programming language.
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Lab: Introduction to Hugging Face, Gradio, and Fine-Tuning a Model - Get an overview of the Hugging Face library, learn to create interactive ML models with Gradio, and learn how to fine-tune a pre-trained model.
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Lab: Understanding Convolutional Neural Networks (CNN) Configurations - Delve into various popular configurations of CNNs, understand their structures, learn how to implement them using TensorFlow, and analyze their applicability to different types of problems.
All the labs in this repository are designed to run on Google Colab. Google Colab is a free cloud-based Jupyter notebook environment that allows you to write and execute Python code and comes preinstalled with many libraries, allowing you to start coding without any setup. It also provides free access to computing resources (including GPUs), which is beneficial for running deep learning models.
Here are some of the benefits of using Google Colab:
- No setup required
- Free access to GPUs
- Easy sharing of your work
- Collaboration with others in real time
- Click on the lab that you're interested in.
- If you're new to Google Colab, check out the Getting Started Guide.
- Once you're comfortable with Google Colab, you can start running the cells in the notebook. Remember that you can edit the code in the cells to understand what each part does. Don't hesitate to break things – the best way to learn is by making mistakes!
This README and the lab assignments were prepared using GPT-4, a large language model developed by OpenAI. The model is trained to generate human-like text based on the input it's given. If you're interested, you can read more about it here.
Happy coding!