Senthilkumar J.

Hello, this is Dr J.Senthilkunar, Chennai, Tamilnadu, India. I have around 19 years experience for both teaching and research. Including around 12 years teaching experience in the Department of Computer Science and Engineering, College of Engineering, Guindy Campus, Anna University, Sardar Patel Road, Chennai-600025, Tamilnadu, India. My area of Interest is Intelligent System, Data Science, Data Analytics and Machine Learning with Python Programming Language, Algorithm Analysis, Programming and Data Structure, Theoretical Computer Science and Operating Systems. There are some interesting types of Inferential Statistics Techniques are useful for Data Science, Data Analytics and Machine Learning fields such as, *1) One sample test of difference/One sample hypothesis test, 2) Confidence Interval, 3) Contingency Tables and Chi Square Statistic, 4) T-test or Anova, 5) Pearson Correlation, Bi-variate Regression, Multi-variate Regression, etc... * And some interesting Data Science, Data Analytics, Artificial Intelligence and Machine Learning algorithms deals with both theoretically as well as practically such as 1) Data Preprocessing Techniques (Binning, Z Score Normalization, Feature Discretization Techiques, Dimension Reduction(Feature Selections - Filter, Wrapper and Hybrid) Algorithms 2) Linear and Logistic Regression Methods 3) Decision Tree Classification (Entropy/Information(ID3 and C4.5), Gini Index) Algorithms 4) Random Forest Classification Algorithm 5) K-Neatest Neighbors (KNN) Classifier 6) Gaussian Navie Bayes Classifier 7) Support Vector Machine (SVC and LinearSVC) 8) Artificial Neural Network (Back Propogation and Feed Forward) Classifiers. Deep Learning with Tensorflow-GPU and PyTorch. 9) Clustering (Partitional Clustering (K-Means Clustering, K-medoids clustering, Mean-Shift Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Expectation–Maximization (EM) Clustering using Gaussian Mixture Models (GMM)), Agglomerative Hierarchical Clustering, and Incremental Clustering) Algorithms. 10) Mining Algorithms (Apriori, Frequent Patteren(FP) Growth, Density FP Groth, etc) In addition to the above I have very good knowledge in the area of 1) Theoretical Computer Science, Programming and Data Structure, Compiler design 2) Programming Languages like Python, R, C, C++, Java *3) Tools like Weka, IBM BI, RapidMiner, Matlab, Octave, PyTorch, TensorFlow etc. I will support one to one online tutoring or home tuition so that the students get clear in each points. I have very good knowledge in the area of Theoretical Computer Science, Programming and Data Structure, Compiler design and Programming Languages like Python, R, C, C++, Java, and some Tools like Weka, IBM BI, RapidMiner, Matlab and Octave. Kindly let me know your willingness. I am waiting your response. Please contact me at WhatsApp No.: 9344591196 Mail_id: [login to view URL] Thanks & Regards. Dr Senthilkumar