Requirements for this Workshop:
- Python Programming
- Anaconda 3 for Built-in Dependencies for Machine Learning
- Jupyter Notebook as Programming Environment
- Tensorflow (Used in Session 3 & 4)
Outline of Workshop:
Session 1:
1.1 Introduction to Machine Learning
1.2 Intuition for Machine Learning (Part 1)
1.3 Intuition for Machine Learning (Part 2)
Session 2:
2.1 Linear Regression for Prediction
2.1E Linear Regression Exercise
2.2 Logistic Regression for Classification
2.2E Logistic Regression Exercise
2.3 Multi-Class Logistic Regression
Session 3:
3.1 Sci-Kit Learn Demo
3.2 Introduction to Neural Networks
3.3 Tensorflow/Keras (Computer Vision)
Session 4:
4.1 Tensorflow/Keras (Natural Language)
Installing Tensorflow:
1) Open Anaconda Prompt
2) Type in "pip install tensorflow==2.0.0-alpha0"
3) You should get this:
Restart Anaconda/Jupyter Notebook and Test if you can import:
In [1]:
import tensorflow as tf
In [2]:
print(tf.__version__)
In [3]:
import tensorflow.keras as K
In [4]:
print(K.__version__) # tf means Tensorflow Backend