CP-ML&DS FOUNDATION PROGRAM HIGHLIGHTS

CP-ML&DS(Machine Learningand Data Science)

Foundation

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The World of Machine Learning(What, Types, Steps, Applications, Linear Algebra,Calculus and Statistics refresher)

Classification using LogisticRegression(Understanding intuitively Logistic Regressionfor solving classification problems, Apply logisticregression to different datasets using scikit- learn,evaluate performance metrics for classification)

Supervised Machine Learning(Solving a Regression problems Usingscikit-learn for Machine Learning. Understandingbasic concepts of linear regression, its applicationon a data set, Performance Metrics for linearregression model, Regularisation Techniques using Lasso Regression and Ridge Regression)

Classification Using Decision Trees(Understanding Decision tree technique forclassification problems, Project by applying DecisionTree Techniques and comparing the performancewith Logistic Regression techniques)

Clustering(Understanding clustering and types of clustering andusing k-means clustering on real world datasets)

NLP

(Introduction to Natural Language Processing and some useful usecases for Preprocessing and Document similarity)

Exploratory Data Analysis(Need of Data, pre-processing of data, boxplot tovisualize data, data and column relationshipsProject: Performing EDA on different Realworld datasets)

Setting up Environment forMachine Learning(Anaconda, Python introduction, Numpy, Panda,Matpotlib, case studies and relevant exercisesProject: Creating a jupyter notebook and apply statistics and visualization using Pandas andMatplotlib on the Boston Housing Dataset)

Tool Coverage

DEVOPS++ ALLIANCE www.devopsppalliance.org