Machine Learning
Learn to create Machine Learning Algorithms from Data Science experts. Code templates included.
For IT & Computer science Engineers
Course Type
Learn to create Machine Learning Algorithms from Data Science experts. Code templates included.
For IT & Computer science Engineers
Course Type
Topic 1 | Introduction to Machine Learning
Topic 2 | Measure of Central Tendency & Dispersion
Topic 3 | Standard Normal Distribution
Topic 4 | Binomial & Poisson Distribution
Topic 5 |Confidence Interval
Topic 6 | Pre program preparation
Topic 7 | Classification algorithm
Topic 8 | Entropy & KNN
Topic 9 | SVM & Linear classifier
Topic 10 | Logistic regression
Topic 11 | Regression
Topic 12 | Poisson Regression
Topic 13 | Lasso & Ridge Regression
Topic 14 | Survival Analysis
Topic 15 | Hierarchical clustering
Topic 16 | Manhattan Distance
Topic 17 | CLARA
Topic 18 | Word cloud
Topic 19 | Getting started with Python & Packages
Topic 20| Python for: Linear Regression
Topic 21 | Introduction to Text Mining
Topic 22 | Introduction to RNN
Topic 23 | Difference between ANN and RNN
Topic 24| Projects
Course Description
Machine learning is an area of artificial intelligence and computer science that covers topics such supervised learning and unsupervised learning and includes the development of software and algorithms that can make predictions based on data. Machine Learning is implemented where programming or developing an efficient algorithm is problematic or not feasible. Machine Learning is revolutionizing the computing ecosystem.
Course objectives
The objective of this training program is to understand how machines can learn from its past experience which is considered as the core of AI. We focus on creating strong fundamental knowledge sets on building algorithms by mastering the principles of statistical analysis.
Roles in industry
Course Highlights
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