Param302 / 100DaysOfCode-Python

I have started 100 days of code to document my coding journey and stay consistent also for accountability.

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I have started 100 days of code to document my coding journey and stay consistent also for accountability.

I am doing Machine Learning starting from Scratch

Daily Tasks

  1. Day - 0 Numpy πŸ”—
  2. Day - 1 Numpy, Pandas πŸ”—
  3. Day - 2 Pandas, Data Analysis project πŸ”—
  4. Day - 3 Pandas (Grouping & Aggregating Data πŸ”—
  5. Day - 4 Pandas (Cleaning data & Time Series Analysis) πŸ”—
  6. Day - 5 Pandas (Working with different data formats) & Data Analysis project πŸ”—
  7. Day - 6 Linear Algebra (Vectors Basics) & Data Analysis project πŸ”—
  8. Day - 7 Matplotlib library πŸ”—
  9. Day - 8 Matplotlib Library πŸ”—
  10. Day - 9 Linear Algebra (Matrices, Linear Transformations) & Data Analysis project πŸ”—
  11. Day - 10 Matplotlib & Data analysis on Titanic Dataset πŸ”—
  12. Day - 11 Data analysis on Titanic Dataset πŸ”—
  13. Day - 12 Data analysis on Titanic Dataset πŸ”—
  14. Day - 13 Data analysis on Titanic Dataset πŸ”—
  15. Day - 14 Matplotlib Library πŸ”—
  16. Day - 15 Matplotlib LibraryπŸ”—
  17. Day - 16 Matplotlib & Seaborn Library πŸ”—
  18. Day - 17 Seaborn Library & Data Analysis project πŸ”—
  19. Day - 18 Seaborn Library & Data Analysis project πŸ”—
  20. Day - 19 Intro to Machine Learning & House price prediction πŸ”—
  21. Day - 20 Intermediate Machine Learning & House price prediction πŸ”—
  22. Day - 21 Intermediate Machine Learning & House price prediction πŸ”—
  23. Day - 22 Linear Algebra & House price prediction πŸ”—
  24. Day - 23 Statistics & House price prediction πŸ”—
  25. Day - 24 Linear Algebra & Statistics πŸ”—
  26. Day - 25 Feature Engineering & House price preidction πŸ”—
  27. Day - 26 Feature Engineering πŸ”—
  28. Day - 27 Feature Engineering & House price prediction πŸ”—
  29. Day - 28 Linear Algebra & PCA πŸ”—
  30. Day - 29 Linear Algebra & Statistics πŸ”—
  31. Day - 30 Titanic dataset prediction & GHW hackathon πŸ”—
  32. Day - 31 Titanic dataset prediction & GHW hackathon πŸ”—
  33. Day - 32 Titanic dataset prediction & GHW hackathon πŸ”—
  34. Day - 33 Titanic dataset prediction & GHW hackathon πŸ”—
  35. Day - 34 Titanic dataset prediction & GHW hackathon πŸ”—
  36. Day - 35 Regression & Classification Random Forest πŸ”—
  37. Day - 36 Started ML Speicalization course & Revised Mathematics πŸ”—
  38. Day - 37 Supervised vs unsupervised learning and Regression model πŸ”—
  39. Day - 38 Linear Regression and Notations in ML πŸ”—
  40. Day - 39 Linear Regression and it's Cost function πŸ”—
  41. Day - 40 Working of Cost function πŸ”—
  42. Day - 41 Gradient Descent πŸ”—
  43. Day - 42 Completed Week 1 of ML course & Gradient Descent πŸ”—
  44. Day - 43 Linear regression with mutliple variables πŸ”—
  45. Day - 44 Vectorization and Gradient Descent πŸ”—
  46. Day - 45 Feature Scaling πŸ”—
  47. Day - 46 Gradient Descent and Simple Linear Regression code πŸ”—
  48. Day - 47 Feature Engineering and Polynomial Regression πŸ”—
  49. Day - 48 (Week 2 assignment) Linear Regression with Gradient Descent code πŸ”—
  50. Day - 49 Linear Regression code in Python πŸ”—
  51. Day - 50 Logistic Regression and Sigmoid function πŸ”—

About

I have started 100 days of code to document my coding journey and stay consistent also for accountability.


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