WalkSelf · AI, Tech & Engineering · AI & Machine Learning

Deep Learning

Dive into the world of artificial neural networks. Learn to build, train, and optimize deep learning models for complex tasks using frameworks like TensorFlow and PyTorch.

Deep Learning

Build Foundational Neural Networks with Multi-Layer Perceptrons

TensorFlow 2 Fundamentals

Flax and TensorFlow: Deep Learning Basics

Foundations of 3D Machine Learning with PyTorch3D

Attention Mechanisms for Deep Learning

L1 and L2 Regularization: Prevent Overfitting in Machine Learning

Deep Neural Networks: Essential Building Blocks

TensorFlow Data Pipelines: Build Efficient `tf.data` Workflows

Sparse Autoencoders: Feature Learning for Classification

PyTorch Image Models: Efficient Listing and Search

Interpreting AI Models with PyTorch Gradients

Build and Train Your First CNN for Image Classification

Non-Convex Optimization with Adam Algorithm

TensorFlow 2 Fundamentals for Beginners

Transfer Learning for Custom Keras Models

TensorFlow Essentials for Deep Learning

Keras Functional API for Custom Deep Learning Models

Building Image Classifiers with Pretrained CNNs

Foundations of Neural Network Training and Regularization

Gradient Descent for Neural Networks: Core Concepts

Deep Learning Essentials: Build Your First Models

Keras Image Preprocessing for Deep Learning Models

Batch Normalization for YOLO: Stable Deep Learning Training

LSTM Networks for Sequence Prediction