Implementing Deep Learning Algorithms with TensorFlow 2.0

Colleagues, the Implementing Deep Learning Algorithms with TensorFlow 2.0 provides you with a solid understanding of Deep Learning models and use Deep Learning techniques to solve business and other real-world problems. Learn various Deep Learning approaches such as CNN, RNN, and LSTM and implement them with TensorFlow 2.0. You will program a model to classify breast cancer, predict stock market prices, process text as part of Natural Language Processing (NLP),  Skill-based training modules include: 1)  Deep Learning Introduction and Environment Setup, 2) Building First Neural Network for Tabular Data with TensorFlow 2.0, 3) Convolutional Neural Networks with TensorFlow 2.0, 4) Recurrent Neural Network with TensorFlow 2.0, 5) Long Short-Term Memory Networks (LSTM), and 6) Transfer Learning with TensorFlow 2.0.  Basic knowledge of Python is assumed. You will understand what problems Deep Learning and TensorFlow 2.0 have solved and can solve, various Deep Learning model architectures and work with them, apply neural network models, deep learning, NLP, and LSTM to several diverse data classification scenarios, including breast cancer classification; predicting stock market data for Google; classifying Reuters news topics; and classifying flower species.

Enroll today (individuals & teams welcome): https://tinyurl.com/a9utjzxc 

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