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Machine Learning Specialization

Master complete machine learning concepts, algorithms and applications.

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Steps to Machine Learning Specialization

Step 1

Mathematics for Machine Learning

Learn the essential math for ML, starting with linear algebra and statistics. Work with matrices, understand eigenvalues, probability, hypothesis testing, and intermediate to advanced statistics tailored for real-world ML challenges

19 Lessons

Linear algebra for Machine Learning

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Statistics for Data Science

Step 2

Get conversant with data

Learn how to make the data ready for ML model building and drive actionable business insights from the data using extensive EDA..

98 Lessons

Data Pre-processing and EDA

Step 3

Learn popular ML algorithms

Learn regression and classification models from zero to professional level. These are the most popular algorithms used in Data Science problems. .

54 Lessons

Linear Regression and Regularisation

35 Lessons

Classification: Logistic Regression

Step 4

Master advanced ML algorithms

Master advanced machine learning algorithms, the maths behind it, code implementations and application. Also, know the real-life do's and dont's of ML modeling.

58 Lessons

Explaining ML Models: Deep Dive

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Machine Learning Plus

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