Machine Learning with TensorFlow

SpiralTrain BV

In the course Machine Learning with TensorFlow from SpiralTrain participants learn to implement machine learning and deep learning applications with the open source TensorFlow framework.

Price

from €2,550

Level

Not specified

Kind

Training

Subject

Automation and IT, Training and education

More information and registration at SpiralTrain BV

Description

TensorFlow Machine Learning The course Machine Learning with TensorFlow starts with an overview of the basic principles of Machine Learning and an explanation of the differences of Supervised, Unsupervised and Deep Learning. The data types of TensorFlow like vectors, arrays, lists and scalars are treated and the Colab and DataBricks development environments are discussed. Tensors Subsequently the Machine Learning with TensorFlow course pays attention to the central Tensor Data Structure, which can be regarded as a container in which data in N dimensions can be stored. Rank, shape and type of tensors are discussed and TensorFlow operations and sessions are also treated. Neural Networks Special attention is given to neural networks in which both Convolutional and Recurrent Neural Networks are explained. Convolution and Pooling, making connections between Input Neurons and Hidden Layers are also discussed. Model Visualization The Visualization of models with TensorBoard is also part of the Machine Learning with TensorFlow course. Supervised Learning with Linear and Logistic Regression are reviewed and Ensemble techniques and Gradient Boosting are explained.