Notes for Data Science

Some notes I put together while going through data science/python/spark courses. I used nbconvert to make jupyter notebooks into READMEs for easy reference.

SQL:

• SQL Exercise

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Scikit-Learn:

1. Visualization of data.
2. Linear regression.
   • Ecommerce Cutomer
3. Logistic regression.
4. K Nearest Neighbors.
   • KNN Project
5. Support Vector Machine.
   • Iris Flower Project
6. Decision Trees and Random Forest
   • Lending Club
7. K Means Clustering
   • College Admissions
8. Recommender System
9. Extra Projects:
   1. 911 Call
   2. Stock Prices

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More Advanced Machine Learning Stuff:

1. Recommender: memory-based and model-based collaborative filtering
2. Natural Language Processing
3. Yelp Project (NLP)
4. MNIST with TensorFlow using logistic regression
5. TensorFlow DNN Estimator
6. Bank Note Authentication Project

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Spark, Python with Big Data

1. Spark DataFrame
   • DataFrame Project
2. Linear Regression
   • Cruise Ship Project
3. Logistic Regression
   • Churn Customer Project
4. K Means Clustering
   • Hacker Consulting Project
5. Natural Language Processing
6. Recommender
7. Decision_Tree_Random_Forest