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Machine Learning - Coggle Diagram
Machine Learning
Projects
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- Perform EDA with SweetViz
- End to End project till deployment
- Deploy ML models using StreamLit
- Perform Exploratory Data Analysis
- Pandas - EDA in single line of code
- Read Huge Datasets using Vaex
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- Interview Prep - for SVM Imp Ques
- Google datasets search engine
Search All datasets from one place for DS
- Run Flask in google colab
- Time Series Forecasting using FB FbProphet
- Performance metrics Interview Question
- Train ML using CPU multi cores
- How to perform post Pruning in Decision Tree
- 6 healthcare End to End ML projects - Credits Devansh and Benanth
- 500+ ML and DL projects at one Place
- Amazing DS end to end project from starters in ML and DL Agriculture domain
Python
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- List, Boolean Variable, Sets , Dictionaries and Tuples
- Numpy and inbuild functions
- Pandas (data frames, Data Series, Reading CSV, Various Parameter, Reading JSON HTML and Pickel
- Matplot (simple visualization library)
- Seaborn (Dist, join, pair plot, Count, Violin and Box plot
- Exploratory Data Analysis (with Titanic dataset)
- Python Functions, Positional, KeyWord Arguments, Lambda function, Map function, Filter functions
- Python List comprehension and Advance String Formating
- Python Iterables vs Iterators
- Importing all important data science libraries using Pyforest
- OOPS - Classes, Variables, Methods and Objects
- Exception Handling and Custom Exception Handling
- Public, Private and Protected Access Modifiers
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Best practices
- Step by Step to learn ML efficiently
- Data Science is just not about model building
- How to Interpret the ML model? Is your model Black box? Lime Library
- Overfitting, Underfitting and data leakage
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- Google Colab Pro vs Colab free
- Advance Python Series - Magic methods in Classes &
Assert Statement in Python
- How to Speed up Pandas by 4X times Modin Pandas Lib
- TextBlob Library in Python for NLP
- 3000+ Research datasets for ML researchers by Papers with code
- Introduction to ML flow-Open source platform for ML lifecycle
- SVM kernal - Polynomial and RBF Implementation using SKlearn ML
Other
- FInd optimal Threshold for Binary Classification
- Bayes Theorem Conditional Probability
- Naive Bayes Classifier (eg NLP)
- Support Vector Machine (SVM)
- SVM Kernels (Polynomial Kernels)
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EDA
- Univariate, Bivariate and Multivariate Analysis
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- Probability Density Function and CDF-EDA
Models / Algorithms
Classification
- Performance Metrics for Classification Problems
- Logistic Regression and Multiclass Classification(One vs Rest) (Intuition and Scikit Learn)
- Decision Tree - Entropy in DT Intuition, Information Gain, Gini Impurity Intuition, Split for Numerical Feature
- House Pricing Prediction Feature
- Performance Metrics on Multi Class Classification Problems
- K Nearest Neighbor (Intuition and Scikit Learn)
- Ensemble: What is Bagging (Bootstrap Aggregation)
- Random Forest Classifier and Regressor
- Handling Imbalanced dataset using Python
- Hyperparameter Optimization for XGBoost, Adaboost (boosting Techniques)
- Visibility Climate Prediction (good one for Resume)
- Euclidean Distance and Manhattan Distance
Regression
- Ridge and Lasso Regression (Intuition, Scikit Learn and Keras)
- Multiple and Multi Collinearity in Regression (Intuition, Scikit Learn and Keras)
- Linear Regression (Intuition, Scikit Learn and Keras)
Statistics
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- R Square and Adjusted R Square
- Hypothesis Testing, Type 1 Error, Type 2 Error
- P Value, T Test, Correlation Implementation, Chi Square Test
Clustering
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- Silhouette (Clustering) - Unsupervised
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- Dimensional Reduction
(Principle component Analysis)
- Principle Component Analysis
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- Cross validation and its types