Sanjeev Mohan Email & Phone Number

Implemented entire Life Cycle of Machine Learning, Gathering Data, Data preparation, Data Wrangling, Analyze Data, Train the model, Test the model & Deployment(basics)Solid ability to develop Supervised Machine Learning Algorithms of Classification, Regression, and Unsupervised Learning Algorithm, Clustering and Association.Skilled in Classification Algorithm Types Binary Classifier, Multi-class Classifier and Problems with Lazy Learners, Eager Learners.Developed predictive models with K-Nearest Neighbor (KNN) Algorithm in Machine Learning, Euclidean Distance, Fitting the K-NN algorithm to the Training Set, Predicting the Test Result, Test Accuracy of the Result (Creation of Confusion Matrix), Visualizing the Test Set Result and Improve the Performance of the K-NN ModelWorked with Naive Bayes Classifier Algorithm in Machine Learning, Bayes Theorem, Posterior Probability, Likelihood Probability, Prior Probability, Marginal Probability, Gaussian Naive Bayes Classifier, Multinomial Naive Bayes Classifier, Bernoulli Naive Bayes Classifier.Worked in Random Forest Classifier Algorithm in Machine Learning, Ensemble Techniques, Bagging (Bootstrap Aggregation)Excellent Knowledge of Regression Algorithms in Machine Learning, Linear Regression, Logistic Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, Random Forest RegressionStatistics Terms and Definitions, Types of Data, Data Measurement Scales, Normalization, Standardization, Measure of Distance, Euclidean Distance, Probability Calculation – Independent & Dependent, Entropy, Information Gain, Regressionin advanced data structures in python like List, Tuple, Set, Frozen set, Skilled Dictionary, Built-in Functions, Lambda Functions and created many user-defined functions in python and RExcellent understanding of NumPy Environment concepts like N-Dimensional Array (Nd array), data types, Slicing & indexing, String Functions, Mathematical Functions, Trigonometric Functions, Rounding Functions, Statistical functions & Linear AlgebraBasic Understanding and Execution of Data warehousing, ETL process(Talend) for the big data analyticsBasic working understanding on Data structures and Algorithms.

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  Government Engineering College Chamarajanagara

  Mechanical Engineering