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A beginners guide to learn Machine Learning from scratch. Learn various algorithms and techniques using ML libraries.
What you’ll learn
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Learn how to use NumPy to do fast mathematical calculations
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Learn what is Machine Learning and Data Wrangling
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Learn how to use scikit-learn for data-preprocessing
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Learn different model selection and feature selections techniques
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Learn about cluster analysis and anomaly detection
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Learn about SVMs for classification, regression and outliers detection.
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 detection.
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Essential NumPy
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Essential Pandas for Machine Learning
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7 hours on-demand video
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Full lifetime access
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Access on mobile and TV
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Certificate of completion
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:
- Introduction to Machine Learning & Data Wrangling
- Linear Models, Trees & Preprocessing
- Model Evaluation, Feature Selection & Pipelining
- Bayes, Nearest Neighbours & Clustering
- SVM, Anomalies, Imbalanced Classes, Ensemble Methods
For the code explained in each lecture, you can find a GitHub link in the resources section.
- 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
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