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Learn_Data_Science_in_100Days

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A step-by-step tutorial to learn Data Science

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Name		Name	Last commit message	Last commit date
.ipynb_checkpoints		.ipynb_checkpoints
Article Published		Article Published
Data		Data
Day01 - Anaconda Installation		Day01 - Anaconda Installation
Day02 - Variable and String		Day02 - Variable and String
Day03 - Numeric, Boolean and Operator		Day03 - Numeric, Boolean and Operator
Day04 - List and Tuple		Day04 - List and Tuple
Day05 - Sets and Dictionary		Day05 - Sets and Dictionary
Day06 - If-Then-Else and Loop		Day06 - If-Then-Else and Loop
Day07 - Functions and Lambda Functions		Day07 - Functions and Lambda Functions
Day08 - Pandas Intro, Read and Write Dataframe		Day08 - Pandas Intro, Read and Write Dataframe
Day09 - Index, Selection and Assignment		Day09 - Index, Selection and Assignment
Day10 - Iteration and Sorting		Day10 - Iteration and Sorting
Day11 - Aggregation and GroupBy		Day11 - Aggregation and GroupBy
Day12 - Missing Values and Handling Them		Day12 - Missing Values and Handling Them
Day13 - Rename and Replace		Day13 - Rename and Replace
Day14 - Merging, Joining and Combine		Day14 - Merging, Joining and Combine
Day15 - Summary, Crosstab and Pivot		Day15 - Summary, Crosstab and Pivot
Day16 - Date, Categorical and Sparse Data		Day16 - Date, Categorical and Sparse Data
Day17 - Pandas Visualizations		Day17 - Pandas Visualizations
Day18 - Numpy Introduction		Day18 - Numpy Introduction
Day19 - Indexing, Slicing, Join and Split		Day19 - Indexing, Slicing, Join and Split
Day20 - Iteration, manipulation, Radom and Distribution		Day20 - Iteration, manipulation, Radom and Distribution
Day21 - NumPy Operations		Day21 - NumPy Operations
Day22 - Sort, Search and Filter		Day22 - Sort, Search and Filter
Day23 - Visualization Part 1 - Basics matplotlib		Day23 - Visualization Part 1 - Basics matplotlib
Day24 - Visualization Part 2 - Matplotlib		Day24 - Visualization Part 2 - Matplotlib
Day25 - Visualization Part 3 - Seaborn and Interactive Charts		Day25 - Visualization Part 3 - Seaborn and Interactive Charts
Day26 - Intro to Stats and Sampling		Day26 - Intro to Stats and Sampling
Day27 - Descriptive Stats		Day27 - Descriptive Stats
Day28 - Relationship Stats and Distribution		Day28 - Relationship Stats and Distribution
Day29 - Central Limit Theorem		Day29 - Central Limit Theorem
Day30 - Inferential Stats		Day30 - Inferential Stats
Day36 - DB Concepts - Normalization and ER Design		Day36 - DB Concepts - Normalization and ER Design
Day37 - Table Creation and Data Loading		Day37 - Table Creation and Data Loading
Day38 - Basic Queries and Filtering		Day38 - Basic Queries and Filtering
Day39 - Join and Union		Day39 - Join and Union
Day40 - SubQueries - Sequencing and Other Functionalities		Day40 - SubQueries - Sequencing and Other Functionalities
Day41-43 - EDA and Feature Engineering using Titanic Dataset		Day41-43 - EDA and Feature Engineering using Titanic Dataset
Day44 - SweetViz		Day44 - SweetViz
Day45 - D-Tale		Day45 - D-Tale
Day46 - Log Transformation		Day46 - Log Transformation
Day47 - One Hot Encoding		Day47 - One Hot Encoding
Day48 - Scaling		Day48 - Scaling
Day49 - Binning		Day49 - Binning
Day50 - EDA and Feature Engineering Wrap-up		Day50 - EDA and Feature Engineering Wrap-up
Day51-52 - Linear Regression Concept and Implementation		Day51-52 - Linear Regression Concept and Implementation
Day53-54 - Logistic Regression Concepts and Implementation		Day53-54 - Logistic Regression Concepts and Implementation
Day55-56 - Decision Tree Implementation		Day55-56 - Decision Tree Implementation
Day57-58 - SVM Concept and Implementation		Day57-58 - SVM Concept and Implementation
Day59-60 - Random Forest Concept and Implementation		Day59-60 - Random Forest Concept and Implementation
Day61-62 - Measuring Model Accuracy		Day61-62 - Measuring Model Accuracy
Day63 - K Fold Cross Validation		Day63 - K Fold Cross Validation
Day64-65 - Bagging and Boosting		Day64-65 - Bagging and Boosting
Day66-67 - K Means Clustering		Day66-67 - K Means Clustering
Day68-69 - Hierarchical Clustering		Day68-69 - Hierarchical Clustering
Day70-71 - Fuzzy C-Means		Day70-71 - Fuzzy C-Means
Day72-73 - Market Basket Analysis		Day72-73 - Market Basket Analysis
.DS_Store		.DS_Store
README.md		README.md

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Learn_Data_Science_in_100Days

A step-by-step tutorial to learn Data Science

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A step-by-step tutorial to learn Data Science

89 stars

8 watching

Report repository

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