Welcome to the Machine Learning Algorithms from Scratch repository! This project contains implementations of various machine learning algorithms, aimed at providing a clearer understanding of how these algorithms work under the hood.
This repository currently includes:
- Attention Mechanism: An implementation of the Attention mechanism from scratch, which is a key component in many modern neural network architectures, particularly in natural language processing (NLP) tasks.
| Topic | Notebook Link |
|---|---|
| Linear Regression Scratch | Linear-Regression-Scratch.ipynb |
| Logistic Regression Scratch | Logistic-Regression-Scratch.ipynb |
| K-Means Clustering Scratch | K-Means-Clustering-Scratch.ipynb |
| Attention Mechanism Notebook | TF_1-Attention_from_scratch.ipynb |
| Simple Perceptron Network | TF-Simple-Perceptron_from-Scratch.ipynb |
| Manual Backpropagation - Mathematics | Backpropagation-Mathematics.ipynb |
| Simple 2 Layer CNN - Mnist | Simple_CNN_Code_MNIST.ipynb |
| Tweet Sentiment Analysis - LSTM | Tweet_Sentiment_LSTM.ipynb |
A comprehensive day-wise pandas tutorial covering all essential functions and operations:
| Day | Topic | Notebook Link |
|---|---|---|
| Day 0 | Pandas Basics & Installation | Day_0_Pandas_Basics.ipynb |
| Day 1 | Data Selection and Indexing | Day_1_Data_Selection_Indexing.ipynb |
| Day 2 | Data Cleaning and Missing Values | Day_2_Data_Cleaning.ipynb |
| Day 3 | Data Aggregation and Grouping | Day_3_Grouping_Aggregation.ipynb |
| Day 4 | Merging, Joining, and Reshaping | Day_4_Merging_Joining.ipynb |
| Day 5 | DateTime and Time Series | Day_5_DateTime_TimeSeries.ipynb |
| Day 6 | File I/O Operations | Day_6_File_IO.ipynb |
| Day 7 | Data Visualization | Day_7_Visualization.ipynb |
| Day 8 | Performance Optimization | Day_8_Performance_Optimization.ipynb |
| Day 9 | Advanced Techniques | Day_9_Advanced_Techniques.ipynb |
| Day 10 | Capstone Project | Day_10_Capstone_Project.ipynb |
Complete 10-day comprehensive pandas tutorial series covering all essential and advanced topics!