Day-1 Introduction, Python Installation, Syntax, variables, data types



Day-1 Introduction, Python Installation, Syntax, variables, data types

Day-1 Introduction, Python Installation, Syntax, variables, data types

1 Month Internship in Machine Learning
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Day – 1: Introduction, Python Installation, Syntax, variables, data types
Day – 2: Data types, conditional statements, looping statements
Day – 3: Functions, lambda, class & object
Day – 4: Class & object, Modules/packages/libraries
Day – 5: Machine learning introduction, pathway, data collection
Day – 6: Pandas Library
Day – 7: Exploratory data analysis project with pandas on Sales dataset
Day – 8: Numpy Library
Day – 9: Visualization with Matplotlib & Seaborn Library
Day – 10: Exploratory data analysis project with pandas & visualization libraries
(population dataset)
Day – 11: sci-kit-learn library: Scaling, encoding, handling null values
Day – 12: sci-kit-learn library: Outlier detection & handling, imbalanced dataset
Day – 13: sci-kit-learn library: train test split, feature selection
Day – 14: Machine learning algorithms: linear model, support vector machines
Day – 15: Machine learning algorithms: Decision tree, ensemble algorithms
Day – 16: Machine learning algorithms: Naive Bayes, KNN, clustering algorithms
Day – 17: Hyperparameter optimization, Metrics
Day – 18: Machine learning classification project – Credit card fraud detection
Day – 19: Machine learning Regression project – Calories burnt prediction
Day – 20: Machine learning clustering project – Spotify music recommendation
Day – 21: Deep learning introduction
Day – 22: ANN project – Churn prediction project
Day – 23: RNN, LSTM introduction
Day – 24: Time series analysis introduction
Day – 25: Time series algorithms
Day – 26: Time series prediction project – Carbon dioxide emission prediction
Day – 27: Time series prediction with Neural networks – Stock price prediction
Day – 28: NLP introduction
Day – 29: NLP project – Fake news classification using NLP
Day – 30: NLP project with Neural networks – Movie rating prediction using NLP

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