Keras Crash Course | Deep Learning, Image Modelling, RNNs and More

Unlock the power of deep learning with Keras 🤖 This crash course is your hands-on guide to mastering neural networks using one of the most user-friendly and widely-used frameworks in the deep learning ecosystem. Whether you’re just getting started with artificial intelligence or advancing your model-building skills, this tutorial will walk you through practical techniques for building, training, and optimizing neural networks to solve real-world problems.

In this tutorial, you’ll learn:
How to build neural networks using the Keras Sequential and Functional APIs.
How to classify images using convolutional neural networks (CNNs).
How to model sequential data using recurrent neural networks (RNNs).
How to handle multiple inputs/outputs and create complex model architectures.

🧠 What You’ll Learn in This Course:
Foundations of Deep Learning: Learn regression, binary, and multiclass classification; tune hyperparameters; build autoencoders and use pretrained models for image classification.
Advanced Architectures with Keras Functional API: Design models with multiple inputs and outputs, use shared layers, and implement categorical embeddings for high-cardinality features.
Image Modeling: Master convolutional neural networks (CNNs), explore deep network stacking, and use techniques to evaluate and improve performance on visual data.
Recurrent Neural Networks (RNNs): Work with GRUs and LSTMs, build text classifiers, generate character-level text, and translate sequences using sequence-to-sequence models.

🖇️ Video Highlights
00:00:00 Introduction & Skill Track Overview
00:00:24 Course 1 Intro: Deep Learning with Keras Fundamentals
00:00:54 What is Keras?
00:01:22 Benefits of Keras vs Lower‑Level Libraries
00:02:13 When to Use Neural Networks on Unstructured Data
00:03:03 Feedforward Neural Networks & Backpropagation
00:04:30 Sequential vs Functional API
00:04:52 Building & Summarizing a Sequential Model
00:07:06 Compiling, Training & Predicting with Keras
00:09:36 Binary Classification in Keras
00:13:14 Multi‑Class Classification & Softmax Activation
00:16:09 Multi‑Label Classification Techniques
00:19:50 Callbacks & Plotting Learning Curves
00:21:40 Early Stopping, Checkpoints & Overfitting
00:29:06 Hyperparameter Tuning with RandomizedSearchCV
00:36:25 Inspecting Model Layers & Tensors
00:38:47 Autoencoders for Dimensionality Reduction
00:40:09 Introduction to Convolutional Neural Networks
00:42:38 Using Pre‑trained ResNet50 in Keras
00:43:59 Introduction to LSTMs & Recurrent Neural Networks

🖇️ Resources & Documentation
Take this skill track on DataCamp: https://www.datacamp.com/tracks/keras...
Introduction to Deep Learning with Keras – https://www.datacamp.com/courses/intr...
Advanced Deep Learning with Keras – https://www.datacamp.com/courses/adva...
Image Modeling with Keras – https://www.datacamp.com/courses/imag...
Recurrent Neural Networks for Language Modeling with Keras – https://www.datacamp.com/courses/recu...

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