TensorFlow 2.0 for Deep Learning (Training)

Colleagues, the TensorFlow 2.0 for Deep Learning program provides you with the core of deep learning using TensorFlow 2.0. You’ll learn to train your deep learning networks from scratch, pre-process and split your datasets, train deep learning models for real-world applications, and validate the accuracy of your models. By the end of the course, you’ll have a profound knowledge of how you can leverage TensorFlow 2.0 to build real-world applications without much effort. You will learn to Develop real-world deep learning applications, Classify IMDb Movie Reviews using Binary Classification Model, Build a model to classify news with multi-label, Train your deep learning model to predict house prices, Understand the whole package: prepare a dataset, build the deep learning model, and validate results, Assess the working of Recurrent Neural Networks and LSTM with hands-on examples, and Implement autoencoders and denoise autoencoders in a project to regenerate images. Skill-based training modules: 1) Deep Learning Basics, 2) TensorFlow 2.0 for Deep Learning, 3) Working with CNNs for Computer Vision and Deep Learning, 4) Working with LSTM for Text Data and Deep Learning, 5) Working with RNNs for Time Series Sequences and Deep Learning, 6) Autoencoders EAE and Denoising AE, and 7) Deep Learning Mini-Projects. This program uses a dedicated GitHub workspace.

Enroll today (individuals & teams welcome): https://tinyurl.com/4mu8fyfk 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy