Author: Pengyuan Li 🌰
- My Medium Publication: DIDS
- Dynamic programming
- Brute Force Algorithm and Greedy Algorithm
update on May 27, 2020
This is my personal learning repo of MITx 6.00.2x, it contains my learning note and some of the lecture PDFs.
Learning Python from academic university is harder than you learn it from other boot-camps (like: datacamp....), especially when you want to learn it from MIT. And, no need to say, you'll definitely learn something special from this course. For example, I have never learnt how to design simulations with Python code until I completed this course, although I've completed hundreds MOOCs previously.
I public this repo, but don't just copy and paste my code, please think about my solution, and please, if you find any issue or you have better solution, just send me a pull request. Let's make this repo better together.
There's an old Chinese saying:
书山有路勤为径，学海无涯苦作舟。
Happy learning!
file structure
- Lecture 1 - Optimization and the Knapsack Problem
- Lecture 2 - Decision Trees and Dynamic Programming
- Lecture 3 - Graph Problems
- Lecture 4 - Plotting
- Lecture 5 - Stochastic Thinking
- Lecture 6 - Random Walks
- Midterm Quiz
- Lecture 7 - Inferential Statistics
- Lecture 8 - Monte Carlo Simulations
- Lecture 9 - Sampling and Standard Error 13 of 13 possible points
- Lecture 10 - Experimental Data Part 1 0 of 4 possible points
- Lecture 11 - Experimental Data Part 2 0 of 11 possible points
- Lecture 12 - Machine Learning
- Lecture 13 - Statistical Fallacies
update on Jun 24, 2020
I am working on organize the notes & materials:
- I am adding comments on the code snippets.
- I am moving the pdf documents to markdown format documents.
update on July 10, 2020
Creating a new github repo, going to use github's project board to manage this project.
