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Learn Keras, earn certificates with paid and free online courses from Purdue University, IIM Bangalore, IIT Roorkee, IIT Guwahati and other top universities around the world. Read reviews to decide if a class is right for you.
. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks?
Understand Deep Learning and build Neural Networks using TensorFlow 2.0 and Keras in Python and R
Get up and running with deep learning with keras, a high level deep learning API
Deep Learning & Keras concepts, model, layers, modules. Build a Neural Network and Image Classification Model with Keras
New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.
Learn advanced deep learning concepts including neural networks, VGG, residual connections, autoencoders, and GANs. Explore batch processing, reproducibility, and practical implementation in Keras.
Build and train fully connected neural networks using Keras for various machine learning tasks, including regression, binary classification, and multi-category classification. Learn to optimize, evaluate, save, and deploy models.
Deep Learning lies at the heart of many leading machine learning and artificial intelligence applications. This course, Deep Learning with Keras, shows you how to use Keras to quickly create powerful deep neural networks.
Get a thorough introduction to Keras, a versatile deep learning framework, and learn how to build, deploy, and monitor robust deep learning models.
This in depth training gives you a first hand look at Keras Models. For multi cloud environments, Keras Models is what you need to create the perfect network.
Learn to build, train, and deploy neural networks using Keras API. Covers data preprocessing, CNNs, transfer learning, and model deployment techniques for both front-end and back-end applications.
Explore deep learning concepts and implement models using Keras in Python. Learn about neural networks, CNNs, RNNs, LSTM, and more for practical applications like chatbots.
Learn to create and visualize a Convolutional Neural Network (CNN) in Python, covering key concepts like convolution, pooling, flattening, and dropout with practical examples and code implementation.
Comprehensive guide to building and evaluating machine learning models using Keras, covering data preparation, model creation, training, and performance analysis with practical examples.
Learn to process audio in Keras using Kapre, exploring its advantages, features, and implementation. Discover how to embed audio transformations within deep learning models for optimized GPU-based calculations and easier deployment.
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