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-fundamentals Introduction to Deep Learning with Keras – https://www.datacamp.com/courses/introduction-to-deep-learning-with-keras Advanced Deep Learning with Keras – https://www.datacamp.com/courses/advanced-deep-learning-with-keras Image Modeling with Keras – https://www.datacamp.com/courses/image-modeling-with-keras Recurrent Neural Networks for Language Modeling with Keras – https://www.datacamp.com/courses/recurrent-neural-networks-rnns-for-language-modeling-with-keras 📱 Follow Us on Social Facebook: https://www.facebook.com/datacampinc/ Twitter: https://twitter.com/datacamp LinkedIn: https://www.linkedin.com/school/datacampinc/ Instagram: https://www.instagram.com/datacamp/ #Keras #DeepLearning #CNN #RNN #NeuralNetworks #ImageModeling #LanguageModeling #ArtificialIntelligence #MachineLearning #TensorFlow #AI #DataScience