PickAClass · 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

Tensor Reshaping and Manipulation for Deep Learning

Softmax Function Fundamentals in Neural Network Design

TensorFlow Data Pipelines: Parsing Serialized TFRecords

Structured PyTorch: Class-Based Model Training and Management

Neural Network Testing with the MNIST Dataset

Building Neural Networks with Keras: A Practical Introduction

Robust TensorFlow Model Training with Monitored Training Sessions

Keras Workflow for Building and Training Neural Networks

Building a Neural Network Class in Python from Scratch

Forward Propagation in 3-Layer Neural Networks

PyTorch Datasets: Mini-Batch Training Loops and Data Splits

Digit Recognition with Keras: Build and Evaluate Deep Learning Models

Batch Gradient Descent and Perceptron Training with NumPy

PyTorch Model Tracking with TensorBoard and SummaryWriter

Building Deep Learning Models with Keras: A Beginner's Guide

Understanding Discrete and Continuous Predictions in Perceptrons

Model Optimization and Hyperparameter Tuning in Keras

Regularization and Optimization in Convolutional Neural Networks

Understanding Hidden Layers in Three-Layer Neural Networks

Recurrent Neural Networks and LSTMs: A Conceptual Guide

Preparing MNIST Data for Neural Network Training

Fundamentals of Simple Recurrent Neural Networks

Data Preparation and Scaling for Neural Networks in Python

Optimizing Neural Networks with Mini-Batch Gradient Descent