GDG Cloud Silicon Valley & GitAcademy present you a 3 hour crash course into Machine Learn, NLP, & TensorFlow 2.0

Hour #1: Intro to Machine Learning

What is Machine Learning (ML)?
Common Use Cases for ML
ML Terminology
Types of Learning in ML
Linear Regression
Classifiers in ML
Logistic Regression
Decision Trees/Random Forests
SVMs

Hour #2: What is NLP?

Main steps for NLP
Text normalization
Word vectors
Word embeddings
One-hot encoding
Term frequency
Stemming
Lemmatization
Stop words
What is tf-idf
What is NLTK
NLTK code samples
Other NLP toolkits
Useful NLP algorithms

Hour #3: Intro to TensorFlow 2

What is TensorFlow 2?
Major Changes in TF 2
Working with strings/arrays/tensors
Working with TF 2 @tf.function decorator
Working with TF 2 generators
Working with TF 2 tf.data.Dataset
Datasets in TF 1.x versus TF 2
Working with TF 2 tf.keras
CNNs, RNNs, LSTMs, Bidirectional LSTMs
Reinforcement Learning/TF Agents

Attendees who will derive the most benefit from this session have:
basic knowledge of Python is strongly recommended
a keen interest in Machine Learning
the ability to learn new concepts quickly