Python AI and Machine Learning for Production & Development

The demo covers following concepts:

1. Machine Learning – Giving Computers the Ability to Learn from Data
2. Training Machine Learning Algorithms for Classification
3. A Tour of Machine Learning Classifiers Using Scikit-Learn
4. Building Good Training Sets – Data Pre-Processing
5. Compressing Data via Dimensionality Reduction
6. Learning Best Practices for Model Evaluation & Hyperparameter Optimization
7. Combining Different Models for Ensemble Learning
8. Applying Machine Learning to Sentiment Analysis
9. Embedding a Machine Learning Model into a Web Application
10. Predicting Continuous Target Variables with Regression Analysis
11. Working with Unlabeled Data – Clustering Analysis
12. Implementing a Multi-layer Artificial Neural Network from Scratch
13. Parallelizing Neural Network Training with TensorFlow
14. Going Deeper: The Mechanics of TensorFlow
15. Classifying Images with Deep Convolutional Neural Networks
16. Modeling Sequential Data Using Recurrent Neural Networks

In addition to the preinstalled setup and demos, the VM also comes with:

1. Jupyter notebook for web based interactive development
2. JupyterHub for multiuser notebook environment to allow multiple users to simultaneously do development
3. Remote desktop
4. Visual studio code IDE
5. Fish Shell

The VM is available on :

1. Google Cloud Platform
2. AWS
3. Microsoft Azure