Deep Learning with Python & TensorFlow

Neural networks, CNNs, RNNs, transformers and modern deep learning techniques.

0.0 (0 reviews)
1 students Advanced
Created by System Administrator  ·  18 chapters  ·  5 modules
Free
Full lifetime access
Access on all devices
Mock tests included
Certificate of completion
What You'll Learn
Forward propagation and backpropagation from scratch
TensorFlow 2 and Keras API
Convolutional Neural Networks (CNNs) for image classification
Data augmentation and transfer learning
Recurrent Neural Networks, LSTMs and GRUs
Attention mechanisms and Transformers
Regularisation techniques (dropout, batch norm, L1/L2)
Custom training loops and callbacks
Model saving, deployment and TF Serving
NLP with Keras and Hugging Face
Course Content
5 modules · 18 chapters
Introduction to Neural Networks Preview
Mathematics for Deep Learning Preview
Optimisers & Training Dynamics
Course Description

Build production-quality deep learning models using Python, TensorFlow 2, and Keras. This course takes you from the mathematics of a single neuron all the way to state-of-the-art transformer architectures.

You will implement Convolutional Neural Networks for computer vision, Recurrent Neural Networks for sequences, attention mechanisms, and learn how to deploy trained models as REST APIs.

Your Instructor
A
System Administrator
Course Instructor