Skip to main content
Category
Topics

Deep Learning Tutorials

Learn how to use AI to speed up data analysis and processes in our deep learning tutorials. Upskill with our deep learning tips, tricks, and techniques.
Other topics:
GroupTraining 2 or more people?Try DataCamp for Business

TRIBE v2 Tutorial: Simulating Human Brain Activity from Video, Audio, and Text

Learn how to run Meta's TRIBE V2 model on Google Colab, predict cortical activity from naturalistic stimuli, and visualize the results as interactive 3D brain heatmaps.

April 7, 2026

LSTM Models: A Complete Guide to Long Short-Term Memory Networks

Master the inner workings of LSTM networks, the foundation for modern LLMs. Explore gating mechanisms, gradients, and build a sentiment classifier with PyTorch.

February 11, 2026

Natural Language Processing with BERT: A Hands-On Guide

Learn what natural language processing (NLP) is and discover its real-world application, using Google BERT to process text datasets.

March 20, 2025

PyTorch CNN Tutorial: Build and Train Convolutional Neural Networks in Python

Learn how to construct and implement Convolutional Neural Networks (CNNs) in Python with PyTorch.

February 27, 2025

Kolmogorov-Arnold Networks (KANs): A Guide With Implementation

Learn about Kolmogorov-Arnold Networks (KANs), a new type of neural network with enhanced interpretability and accuracy compared to traditional models.

November 8, 2024

AdamW Optimizer in PyTorch Tutorial

Discover how the AdamW optimizer improves model performance by decoupling weight decay from gradient updates. This tutorial explains the key differences between Adam and AdamW, their use cases and provides a step-by-step guide to implementing AdamW in PyTorch.

October 21, 2024

Adagrad Optimizer Explained: How It Works, Implementation, & Comparisons

Learn the Adagrad optimization technique, including its key benefits, limitations, implementation in PyTorch, and use cases for optimizing machine learning models.

September 26, 2024

PyTorch Lightning: A Comprehensive Hands-On Tutorial

This comprehensive, hands-on tutorial teaches you how to simplify deep learning model development with PyTorch Lightning. Perfect for beginners and experienced developers alike, it covers environment setup, model training, and practical examples.

July 14, 2024

Cross-Entropy Loss Function in Machine Learning: Enhancing Model Accuracy

Explore cross-entropy in machine learning in our guide on optimizing model accuracy and effectiveness in classification with TensorFlow and PyTorch examples.

February 27, 2026

Introduction to Autoencoders: From The Basics to Advanced Applications in PyTorch

A walkthrough of Autoencoders, their variations, and potential applications in the real world.

December 14, 2023

What Are Convolutional Neural Networks? A Complete CNN Guide

A complete guide to understanding CNNs, their impact on image analysis, and some key strategies to combat overfitting for robust CNN vs deep learning applications.

March 26, 2026

Introduction to Activation Functions in Neural Networks

Learn to navigate the landscape of common activation functions—from the steadfast ReLU to the probabilistic prowess of the softmax.

October 31, 2025