What are the fundamentals of Data and Deep Learning.
How to build neural networks and successfully lead Machine Learning projects.
Learn about Convolutionary networks, RNNs, LSTM, Adam Optimization, Dropout, BatchNorm, initialization and much more.
TECHNICAL ORIENTATION
Neural Networks and Deep Learning. Hyper-parameter tuning, regularization and optimization. Convolution Neural Networks. Sequential Models. Introduction to Reinforcement Learning. Transfer Learning, Multitask Learning and End-to-End Learning. Structuring Deep Learning projects. TOOLS
Python, Numpy, KeraS, TensorFlow, TensorBoard, Distributed TensorFlow, TensorFlow Serving. Review of cloud and mobile implementations.
Most Used Hardware CPU, GPU, TPU, FPGA, Mobile Neural Engines
Hi, thanks for your help guys.
Really loved what you did here, been taking the first courses and they are so good. Thrilled to get into programming #Awesome
Comments
Thomas Bethesda 2020-02-19 at 2:36 PM
Hi, thanks for your help guys.
Really loved what you did here, been taking the first courses and they are so good. Thrilled to get into programming #Awesome