Python-Data-Science-and-Machine-Learning-Bootcamp-Projects

My solutions for the projects given in the Udemy course: Python for Data Science and Machine Learning Bootcamp by Jose Portilla. I have listed the topics covered in the course below, and notice that not all of the topics have a project. The instructor also follows the ISLR book along with the Machine Learning topics.

Topics covered:

0. Jupyter Notebook Overview and Basic Python
1. NumPy for Numerical Data
2. Pandas for Data Analysis
3. Matplotlib for Python Plotting
4. Seaborn for statistical plots
5. Plotly (and Cufflinks) for interactive dynamic visualizations
6. Geographical Plotting (Choropleth Maps)
7. 2 Data Capstone Projects including the topics above
8. SciKit-Learn for Machine Learning
   • Cross Validation and Bias-Variance Trade-Off
   • Linear Regression
   • k-Nearest Neighbours
   • Logistic Regression
   • K-Means Clustering
   • Random Forest and Decision Trees
   • Support Vector Machines
   • Principal Component Analysis
9. Natural Language Processing
10. Recommender Systems
11. Neural Networks and Deep Learning
    • Tensorflow
    • Keras
12. Big Data and Spark with Python

Note: The solutions given are my solutions, and they are posted with the permission of the instructor.

Reference:

• Python for Data Science and Machine Learning Bootcamp:
  • Retrieved from https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/