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Google TensorFlow (Machine Learning)

Duration 3 hours:

Format : First half – Lecture /Slides

AI and Deep Learning Introduction:

• Uses and applications

• Techniques

• Bayes Nets

• Supervised Learning

• Unsupervised Learning

Neural Networks

• Neurons

• Weights and Bias

• Activation (Sigmoid)

• Perceptron

• Gradient Descent

• Back propagation

• Examples

Second Half – Hands On Workshop

• Anaconda Environment (Python)

• Hello TensorFlow

• Supervised Classification

• Training the Network

• Example Exercise

Hands on Using Anaconda with TensorFlow installed (see https://www.continuum.io/ (https://www.continuum.io/)

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