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Course Details –:
Published by: Digital University
What you’ll learn
- Learn how to use NumPy to do fast mathematical calculations
- Learn what is Machine Learning and Data Wrangling
- Learn how to use scikit-learn for data-preprocessing
- Learn different model selection and feature selections techniques
- Learn about cluster analysis and anomaly detection
- Learn about SVMs for classification, regression and outliers detectio
Description–
If you are looking to start your career in machine learning then this is the course for you.
This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels.
This course has 5 parts as given below:
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Introduction to Machine Learning & Data Wrangling
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Linear Models, Trees & Preprocessing
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Model Evaluation, Feature Selection & Pipelining
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Bayes, Nearest Neighbours & Clustering
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SVM, Anomalies, Imbalanced Classes, Ensemble Metho
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For the code explained in each lecture, you can find a GitHub link in the resources section.
Who this course is for:
- Beginners who want to become a data scientist
- Software developers who want to learn machine learning from scratch
- Python developers who are interested to learn machine learning
- Professionals who want to start their career in Machine Leaning
Enroll Now -:
Free 12800 100% off
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