Mentorship Repository for Machine Learning Type = Level 1
- Mentor needs to fork this repository
- Mentee needs to joins as a contributor
This template is designed to assist Twoleaps mentorship program. The template consists of two major sections: Goals and Progress tracker. Mentors and mentee should add goals prior to start of mentorship. Goals should be such that both party agree on. Progress tracker is to be updated on week by week basis with new tasks to complete the defined goals. For each week, a folder in the repository has to be maintained which captures the work done. It can be a small essay of things learned or written code etc.
Regular feedback is highly encouraged. Feedbacks should inspire improvement. Mentors should summarize week by week progress in form of feedback whenever possible and add it to the weekly work folder in form of week1/feedback.md
<Add mentorship timeline here in weeks. Example: 8 weeks starting 10th August>
The objectives of the mentorship should be listed down here. They can be customized over time by the mentor or the mentee's preferences.
House Price Prediction
- Linear Model
- Support Vector Machines
- Random Forest
Algorithm | Requirements |
---|---|
Linear Model | Python, Numpy, Pandas, sklearn |
Support Vector Machines | Python, Numpy, Pandas, sklearn |
Random Forest | Python, Numpy, Pandas, sklearn |
- Python Primer
- General Overview
- Variables and Data Types
- Data Structures and Control and Flow
- String Operations and List Comprehensions
- Functions
- Object Orientes Programming
๐ COMPLETION OF FIRST MILESTONE ๐
- Numpy Primer
- General Overview
- Introduction to Numpy Arrays
- Operations on Numpy Arrays
- Manipulation of Numpy Arrays
- File I/O using Numpy
๐ COMPLETION OF SECOND MILESTONE ๐
- Pandas Primer
- General Overview
- Pandas Data Structures
- Data Selection and Inspection
- Data Reshaping and Cleaning
- Data Grouping
- Join/Combine Datasets
- Data Statistics
- Data Plotting
- File I/O using Pandas
๐ COMPLETION OF THIRD MILESTONE ๐
- Python Libraries
- SciPy
- Matplotlib
- Scikit Learn
- NLTK
๐ COMPLETION OF FOURTH MILESTONE ๐
- Final Project
- Implementaion using Linear Model
- Implementation using SVM
- Implementation using Random Forest
๐ FINAL MILESTONE ๐
Track weekly progress in this section according to above mentioned goals.
-
- Task 1
- Task 2
- Task 3
- Task 4
- Task 5