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