Machine Learning using Python

• Adding python code for various Machine Learning problems

Categories:

1. Supervised Learning
2. Unsupervised Learning
3. Clustering
4. Artificial Neural Network (ANN)
5. Convolution Neural Network (CNN)
6. NLP
7. Text Classification & Mining

Sub categories

1. EDA - Exploratory Data Analysis
2. Visualization
3. Model fine tuning
4. Model deployment
5. Model integration (including SAP, Salesforce)

Python Installation and Execution

• In order to get the development environment running, Python v3 (latest version) needs to be installed in the machine.
  • Python 3.7.0: https://www.python.org/downloads/release/python-370/
• Clone the repository and open terminal from project directory.
• Create a virtual environment for installing dependencies. A new directory gets created. python3 -m venv .myenv
• Activate it using the source command. Notice the environment name (.myenv) in terminal after executing this. source .myenv/bin/activate
• Navigate into the cloned folder (cd MachineLearning)
• Install the requirements using pip command. pip install -r requirements.txt
• Install Jupyter lab or notebook pip install jupyterlab or pip install notebook
• Run Jupyter lab or notebook jupyter lab or jupyter notebook
• Open the file and play around

Where to find data?

Online Data Science Competitions platforms etc

1. kaggle – Online datascience competitions ( from google) ( kaggle.com )
2. Online Data Science competitions - https://www.drivendata.org/competitions/
3. Quantopian: A Quant Finance platform where you can run your python scripts on financial data ( mostly secondary markets ) - www.quantopian.com

Code & Research Papers

1. Papers With Code highlights trending ML research and the code to implement it. (www.Paperswithcode.com)
2. Github - The code repository where you can find almost all types of code
3. Stackoverflow - online community for developers - ask your doubts here. You will hit this invariably
4. Arxiv.org - A good repository of academic pre-prints & latest works in ComputerScience & More recently on AI/ ML

Why Visualization

Data Visualization by Hans Rosling https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seen

More about markdown editor

Online Markdown editor (https://dillinger.io/ )

Algorithm Cheat sheet

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### Happy Learning