GitHub - farhanzafrani/100-days-of-machine-learning: One the best Resources to learn Machine Learning from Scratch. They also have a YOUTUBE channel where they teach all the things.

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One the best Resources to learn Machine Learning from Scratch. They also have a YOUTUBE channel where they teach all the things.

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Name		Name	Last commit message	Last commit date
Latest commit History 152 Commits
day15 - working with csv files		day15 - working with csv files
day16 - working-with-json-and-sql		day16 - working-with-json-and-sql
day17-api-to-dataframe		day17-api-to-dataframe
day18-pandas-dataframe-using-web-scraping		day18-pandas-dataframe-using-web-scraping
day19-understanding-your-data-descriptive-stats		day19-understanding-your-data-descriptive-stats
day20-univariate-analysis		day20-univariate-analysis
day21-bivariate-analysis		day21-bivariate-analysis
day22-pandas-profiling		day22-pandas-profiling
day24-standardization		day24-standardization
day25-normalization		day25-normalization
day26-ordinal-encoding		day26-ordinal-encoding
day27-one-hot-encoding		day27-one-hot-encoding
day28-column-transformer		day28-column-transformer
day29-sklearn-pipelines		day29-sklearn-pipelines
day30-function-transformer		day30-function-transformer
day31-power-transformer		day31-power-transformer
day32-binning-and-binarization		day32-binning-and-binarization
day33-handling-mixed-variables		day33-handling-mixed-variables
day34-handling-date-and-time		day34-handling-date-and-time
day35-complete-case-analysis		day35-complete-case-analysis
day36-imputing-numerical-data		day36-imputing-numerical-data
day37-handling-missing-categorical-data		day37-handling-missing-categorical-data
day38-missing-indicator		day38-missing-indicator
day39-knn-imputer		day39-knn-imputer
day40-iterative-imputer		day40-iterative-imputer
day42-outlier-removal-using-zscore		day42-outlier-removal-using-zscore
day43-outlier-removal-using-iqr-method		day43-outlier-removal-using-iqr-method
day44-outlier-detection-using-percentiles		day44-outlier-detection-using-percentiles
day45-feature-construction-and-feature-splitting		day45-feature-construction-and-feature-splitting
day47-pca		day47-pca
day48-simple-linear-regression		day48-simple-linear-regression
day49-regression-metrics		day49-regression-metrics
day50-multiple-linear-regression		day50-multiple-linear-regression
day51-gradient-descent		day51-gradient-descent
day52-types-of-gradient-descent		day52-types-of-gradient-descent
day53-polynomial-regression		day53-polynomial-regression
day55-regularized-linear-models		day55-regularized-linear-models
day56-lasso-regression		day56-lasso-regression
day57-elasticnet-regression		day57-elasticnet-regression
day58-logistic-regression		day58-logistic-regression
day59-classification-metrics		day59-classification-metrics
day60-logistic-regression-contd		day60-logistic-regression-contd
day65-random-forest		day65-random-forest
day66-adaboost		day66-adaboost
day68-stacking-and-blending		day68-stacking-and-blending
gradient-boosting		gradient-boosting
kmeans		kmeans
adaboost_demo.ipynb		adaboost_demo.ipynb
day68-stacking		day68-stacking