Introduction to machine learning * Supervised and unsupervised learning * Statistical learning and regression * Curse of dimensionality and parametric models * Classification problems, K Read More …
Category: Professional Courses
Deep Learning
1. Computer vision overview and historical context 2. Image Classification using traditional approaches 3. Introduction to Multi-layer perceptron, Neural Network, Introduce hardware for deep learning Read More …
Data Science With Python
Introduction to Python Data Pre-Processing Techniques Introduction to basic Python syntax and structure K-Mean Clustering (Solved Example) Implementation of K Mean in python KNN Clustering Read More …
Big Data Fundamentals
Introduction to big data Introduction to Apache Spark Machine learning with Spark Introduction to Hadoop Understanding MapReduce MapReduce concepts Apache Yarn Oozie and Sqoop in Read More …
IBM SPSS Statistics Software
Introduction Data Entry and Data Transformation Quantitative Data Analysis Coding & Commuting new Variables Testing Data Normality Parametric & Non-Parametric Analysis One Way ANOVA & Read More …