Mathematics & Statistics for Machine Learning
What you'll learn
- You will understand the fundamentals of mathematics and statistics relevant for machine learning
- You will gain insights on the application of math and stats on machine learning
- You will know what problems Machine Learning can solve, and how the Machine Learning Process works
- You will learn Measures of Central Tendency vs Dispersion
- You will understand Mean vs Standard Deviation & Percentiles
- You will have clarity on the Types of Data & Dependent vs independent variables
- You will be knowledgeable on Probability & Sample Vs population
- You will gain clarity on Hypothesis testing
- You will learn the Types of distribution & Outliers
- You will understand the maths behind algorithms like regression, decision tree and kNN
- You will gain insights on optimization and gradient descent
Requirements
- No prior experience is required. We will start from the very basics.
Description
The trainer of this course is an AI expert and he has observed that many students and young professionals make the mistake of learning machine learning without understanding the core concepts in maths and statistics. This course will help to address that gap in a big way.
Since Machine Learning is a field at the intersection of multiple disciplines like statistics, probability, computer science, and mathematics, its essential for practitioners and budding enthusiasts to assimilate these core concepts.
These concepts will help you to lay a strong foundation to build a thriving career in artificial intelligence.
This course teaches you the concepts mathematics and statistics but from an application perspective. It’s one thing to know about the concepts but it is another matter to understand the application of those concepts. Without this understanding, deploying and utilizing machine learning will always remain challenging.
You will learn concepts like measures of central tendency vs dispersion, hypothesis testing, population vs sample, outliers and many interesting concepts. You will also gain insights into gradient decent and mathematics behind many algorithms.
We cover the below concepts in this course:
Measures of Central Tendency vs Dispersion
Mean vs Standard Deviation
Percentiles
Types of Data
Dependent vs independent variables
Probability
Sample Vs population
Hypothesis testing
Concept of stability
Types of distribution
Outliers
Maths behind machine learning algorithms like regression, decision tree and kNN
Gradient descent.
Who this course is for:
- Data Scientists, Python Programmers, ML Practitioners, IT Managers managing data science projects
Course content
- Preview02:32
Instructors
![Govind Kumar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 639 Reviews
- 56,468 Students
- 19 Courses
Summary:
Over 2 decades of experience managing Technology, Operations and Quality in top MNCs & startups. Held leadership roles and managed businesses across Asia Pacific & Japan region
Expertise: AI, Six Sigma and Innovation
Key Experiences:
Successfully incubated Centers of Excellence for fraud prevention and service analytics.
Significant experience in design thinking based product development and management. Played a critical role in developing products for emerging markets.
Education & Certification:
B. Tech and Full time MBA from top institutes in India
Certifications in six sigma and project management.
Accolades:
Won global awards in the areas of Customer Experience, Leadership Excellence, Quality and Technology.
Featured in the cover of CIO Review Magazine.
Current Role: Founder & CEO of SeaportAI.
Board of Studies: Member of the Board of Studies at Loyola College, Chennai, India (a 96 year old institution)
- 4.1 Instructor Rating
- 4,865 Reviews
- 273,102 Students
- 42 Courses
We specialize in Cybersecurity, Data Science and Talent Management/Human capital management training. The USP of all our training's is the hands-on that we provide, our focus is on real-life practical knowledge sharing, and not tool-based PPT slides. All our training's are conducted by highly experienced practitioners who are dyed-in-the-wool penetration testers. The material is cutting edge and updated with even the most recent developments. We have a standard set of courses outlined in different information security domains, data analytics domains and Talent management domain. However, we also customize the training according to the clients’ requirements.