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Machine-Learning

Titanic ,LSTM ,CNN

Titanic

Implementation: i. Import Titanic Dataset. ii. Data Cleaning: Use an appropriate method to handle missing value iii. Feature engineering: iv. Perform exploratory data analysis (EDA) using, plot histogram, derive variance, Pearson correlation coefficient matrix, Features density plots (indicating Central tendency and spread) of every feature grouped by class label, Box Plot for every feature v. Feature scaling vi. Data Pre-processing: (1) Feature selection using Information Gain (IG) (2) Feature extraction using Principle Component Analysis (PCA). vii. Perform Classification task with and without feature selection using classifiers (Bayes Classifiers, Logistic regression, K-nearest classifier). Do comparative study on mentioned classifiers using evaluation metrics (Precision, Recall, F1 Score) in tabular form.

LSTM

Implement LSTM for data set (Google_Stock_Price)

CNN

Implement CNN to classify following data sets: Cat vs Dog Dataset Download link: https://www.microsoft.com/en-us/download/details.aspx?id=54765

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Titanic ,LSTM ,CNN

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