Learn the concepts of Machine Learning and effective techniques using Python. This course includes multiple lab sessions and real-world projects from Industry experts. Recommended for beginners and working professionals.
Find out about the concepts of Machine Learning, effective machine learning techniques from basics with Python.
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This course is the perfect place for beginners to comprehend the core thought of building systems that can automatically gain from data and work on the experience without being explicitly programmed. In this course, you will find out about concepts of Machine Learning, effective machine learning techniques, and gain practice executing them and inspiring them to work for yourself all in a classroom program. The course will be tutored and directed by Industry experts having active experience in ML-based industry projects. The course includes 1 major and 3 minor projects based on real-world applications with directed lab sessions.
Ought to know the basics of any one programming language
Active on python.
Basic punctuation and data structures in python
Introduction to data frames, numpy, pandas and different libraries in python.
Introduction to ML
Sorts of problems addressed by ML.
Real world scenarios where ML is applicable.
Basic Wording utilized in ML through a case study.
Building Regression models like Linear Regression, its variants etc.
Assessing regression models, assessment metrics, cost function etc.
Project 1 (Lab meeting)
Predicting House prices
Introduction to classification techniques.
Logistic Regression, Decision Trees, Random Forests.
Assessing Classification Models.
Project 2 (Lab meeting)
Inn Surveys Data Sentiment Analysis
Clustering and Similarity techniques
Other clustering Algorithms :
Apriori Algorithm etc
Project 3 (Lab meeting)
Clustering 2D points through K-Means Algorithm
Introduction to Deep Learning
Best Practices while planning Machine Learning Solutions
Real-time Ads Recommendation System
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