Machine Learning Essentials - Master core ML concepts
What you'll learn
- Jumpstart the world of AI & ML
- Maths of Machine Learning
- Regression & Classification Techniques
- Linear & Logistic Regression
- K-Nearest Neighbours, K-Means
- Naive Bayes, Text Classification
- Decision Trees & Random Forests
- Ensemble Learning - Bagging & Boosting
- Dimensionality Reduction
- Neural Networks
- 8+ Hands on Projects
Requirements
- Python Programming
- Basics of Numpy, Pandas, Matplotlib
Description
Read to jumpstart the world of Machine Learning & Artificial intelligence?
This hands-on course is designed for absolute beginners as well as for proficient programmers who want kickstart Machine Learning for solving real life problems. You will learn how to work with data, and train models capable of making "intelligent decisions"
Data Science has one of the most rewarding jobs of the 21st century and fortune-500 tech companies are spending heavily on data scientists! Data Science as a career is very rewarding and offers one of the highest salaries in the world. Unlike other courses, which cover only library-implementations this course is designed to give you a solid foundation in Machine Learning by covering maths and implementation from scratch in Python for most statistical techniques.
This comprehensive course is taught by Prateek Narang & Mohit Uniyal, who not just popular instructors but also have worked in Software Engineering and Data Science domains with companies like Google. They have taught thousands of students in several online and in-person courses over last 3+ years.
We are providing you this course to you at a fraction of its original cost! This is action oriented course, we not just delve into theory but focus on the practical aspects by building 8+ projects.
With over 170+ high quality video lectures, easy to understand explanations and complete code repository this is one of the most detailed and robust course for learning data science.
Some of the topics that you will learn in this course.
Logistic Regression
Linear Regression
Principal Component Analysis
Naive Bayes
Decision Trees
Bagging and Boosting
K-NN
K-Means
Neural Networks
Some of the concepts that you will learn in this course.Convex Optimisation
Overfitting vs Underfitting
Bias Variance Tradeoff
Performance Metrics
Data Pre-processing
Feature Engineering
Working with numeric data, images & textual data
Parametric vs Non-Parametric Techniques
Sign up for the course and take your first step towards becoming a machine learning engineer! See you in the course!
Who this course is for:
- Programmers who are curious to about Machine Learning and Artificial Intellgence
- Working professionals who want to build a career in data science
- Developers who wants to learn a new skill and build ML based projects
- University and college students who want to strengthen their understanding of Machine Learning
Instructors
- 4.5 Instructor Rating
- 3,475 Reviews
- 27,862 Students
- 4 Courses
Mohit is a Data Scientist, programming instructor and co-creator at Coding Minutes. He has trained over 50000+ students in Machine Learning and AI over the last 5 years of his teaching experience. His expertise lies in Python, data science, machine learning and AI, and he has won many competitions. He has been doing AI-based projects for the last 4 years. He also leads the ML and Data Science Domain of Coding Minutes.
- 4.6 Instructor Rating
- 15,337 Reviews
- 128,263 Students
- 12 Courses
Prateek is popular programming instructor and an ace software engineer having worked with Google in the past, currently working with Scaler and created Coding Minutes to bring high quality courses at pocket friendly pricing. He is known for his amazingly simplified explanations that makes everyone fall in love with programming. He has has over 5+ years of teaching experience and has trained over 50,000 students in classroom bootcamps & online course at a popular bootcamp in the past. His expertise lies in problem solving, algorithms, competitive programming and machine learning. His interactive mario style at prateeknarang resume is loved by all. Many of his ex-students are now working in top product companies like Apple, Google, Amazon, PayTm, Microsoft, Flipkart, Samsung, Adobe, DE Shaw, Codenation, Arcesium and more.