2 Days Live Training on Statistics for Data Science & Machine Learning

This course will help you dive in-depth into the knowledge of Statistics for Data Science and Machine Learning . Master core concepts of Statistics, Data Science and Machine Learning. It helps you visualize the data and analyze data to find unseen patterns.

Data Science & Analytics

12 Hours

Description

This course is designed to get an in-depth knowledge of Statistics and Probability for Data Science and Machine Learning point of view. Here we are talking about each and every concept of Descriptive and Inferential statistics and Probability. By completing this course.

Course Objectives

Gain the understanding of Statistical concepts for Machine Learning and Data Science point of view.

Understand the difference between descriptive statistics and inferential statistics.

Derive the Hypothesis and understand the same

Understand the probability concepts for Data Science point of view.

Understand the concepts of Permutation and combinations and how it can be tagged with probability.

Understand and use the hypothesis testing method to drive business decisions

Understand and use linear regression model and relevant key terms

Understand different distributions and its properties

Target Audience

This course is meant for all those students and professionals who are interested in using the Statistics and Probability for Machine Learning and Data Science. 

Basic Understanding

There are no prerequisites

Course Content

No sessions available.

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Simpliv LLC
39658 Mission Boulevard,
Fremont, CA 94539, USA

2 Days Live Training on Statistics for Data Science & Machine Learning

Session 1: Statistics - An Introduction

No lectures available

Session 2: Measure of Central Tendency

No lectures available

Session 3: Measure of Spread - Part 1 (Range, IQR, Variance, Standard Deviation and MAD)

No lectures available

Session 4: Regression - In-Depth

  1. Regression - An Introduction
  2. Covariance and Covariance Matrix
  3. Karl Pearson Correlation Coefficient
  4. Spearman Rank Correlation Coefficient
  5. Residuals
  6. R-Square and RMSE

Session 5: Normal Distribution

No lectures available

Session 6: Statistics - Symmetric Distribution, Skewness, Kurtosis and KDE

No lectures available

Session 7: Probability

No lectures available

Session 8: Permutation and Combination

No lectures available

Session 9: Combinatorics and Probability

No lectures available

Session 10: Random Variables

No lectures available

Session 11: Distributions

  1. Binomial and Bernoulli Distribution - Part 1

Session 12: Sample Distribution and Central Limit Theorem

No lectures available

Session 13: Confidence Interval

No lectures available

Session 14: TStatistic

No lectures available

Session 15: Significance Tests

  1. Significance Tests - An Introduction
  2. Type 1 and Type 2 Errors
  3. Constructing Hypothesis

Session 16: Chi-Squared Distribution

No lectures available

Session 17: Advanced Regression - Inference and Transforming

No lectures available

Session 18: ANOVA and F-Statistic

No lectures available

Coupons

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