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Machine Learning Path,

Step-by-step

A complete overview of machine Learning Space,

understand itâ€™s applications and limitations, and how

projects are undertaken.

Regularly

Updated

Updated

More than

23+ courses

23+ courses

Industry

Projects

Projects

13,715 Sudents

Enrolled

Enrolled

Get early bird price if you Enroll Now!

Regularly

Updated

Updated

More than

26+ courses

26+ courses

Industry

Projects

Projects

115+ Students

Enrolled

Enrolled

Get complete overview of machine Learning Space. Understand itâ€™s

applications and limitations, and how projects are undertaken.

- Foundations of Machine Learning Sessions: 28 2hr 26m
Get complete big picture view of Machine Learning space. Understand its industrial applications and limitations, and how projects are undertaken in mature Data Science teams.Data science beginners start your ML journey here. For Business managers who want to gain a holistic understanding of ML/AI in Industry.

- Complete Python for beginners Sessions: 50 5hr 40m
Python is a powerful general-purpose programming language.It is used in web development, data science, creating software prototypes, and so on.Start with writing the 1st line of code in python and become an expert. Learn the finer practical nuances only experienced programmers know, and practice with 100+ examples and assignments.

- Numpy for Data Science Sessions: 29 3hr 09m
Master the go to/most popular library for complex mathematical operations.

- Pandas for Data Science Sessions: 84 6hr 37m
Pandas is the most popular Python library for data wrangling and analytics. Master Pandas for all future data science projects

- Data Pre-processing and EDA Sessions: 98 7hr 07m
Learn how to make the data ready for ML model building and drive actionable business insights from the data using extensive EDA

- Linear Regression and Regularisation Sessions: 54 7hr 22m
Linear Regression is one of the most widely and foundational regression algorithm of machine learning. Learn how to build a regression model from scratch and how to overcome the problem of overfitting in machine learning. Not just that, learn about various advanced regression algorithms and metrics to evaluate the models.

- Classification: Logistic Regression Sessions: 35 4hr 47m
Learn how to solve classification problems in data science. Logistic regression is one of the foundational classification algorithms in machine learning. Learn the Ins and Outs of logistic regression theory, the math, in-depth concepts, do's and don'ts and code implementation With crystal clear explanations as seen in all of my courses.

- Imbalanced Classification Sessions: 25 2hr 48m
Have you come across the problem of class imbalance while working on classification problems? Learn how to solve this problem and make classification engines to classify the target variable even on the imbalanced data.

- Supervised ML Algorithms Sessions: 57 7hr 26m
Enjoy learning the intuition, concept and underlying math behind Supervised Learning algorithms with complete clarity and have all your doubts answered. You will learn several nuances and special cases, gain mastery to confidently crack Interviews..

- Ensemble Learning Sessions: 20 2hr 12m
Ensemble method is a machine learning technique that combines several base models in order to produce one optimal predictive model. Learn the detailed maths and intutuion behind these ensemble methods. Solve data science problems effeciently using multiple ensemble algorthms.

- ML Deployment in AWS EC2 Sessions: 19 1hr 59m
Learn how to convert your ML models to a productionizable app. Host it in AWS EC2 instance performed live and learn all the intermediate steps, purpose behind it and best practices.

- Deploy ML Models in AWS Lamda Sessions: 09 52m
Learn how to serve machine learning from AWS Lambda. Undestand the AWS Lambda service, set it up and learn how to deploy ML in Lambda in minutes without provisioning or managing infrastructure.

- Deploy ML Models in AWS Sagemaker Sessions: 09 2h 55m
Learn to Build, Train and Deploy ML Models with AWS Sagemaker in depth. Sagemaker allows you to do production grade deployment and everything you need in ML lifecycle.

Covers sagemaker specific details, industry best practices and fully worked out code with live demonstration.

- Estimating Customer Lifetime Value for Business Sessions: 31 3hr 33m
Learn the theory, concepts and Machine Learning methods on estimating Customer Lifetime Value (CLTV) for businesses.

Explore formula based, ML and probabilistic approaches and implement them using Python. Know about the mistakes to avoid and industry best practices." - Microsoft Malware Detection Project Sessions: 41 4hr 53m
1. Predict whether a system will get infected by Malware or not

2.Work on real Microsoft data like a practising data scientist

3.Build and evaluate multiple modes and gather insights. - Credit Card Fraud Detection Sessions: 51 5hr 12m
1.Build a classification engine which predicts whether a transaction is fraud or not.

2.Work on multiple features on real data set.

3.Explore alternate approaches to modeling and evaluation - Restaurant Visitor Forecasting Sessions: 57 4hr 58m
1.Forecast number of restaurant visitors using multiple strategies.

2.Gain knowledge of basic to advanced statistical tools and advanced ML modeling techniques.

3.Understand concepts from scratch and implement the project - Optimizing marketing spend using Market Mix Modeling (MMM) Sessions: 35 4hr 20m
1.Learn how to implement the core Market Mix Modeling (MMM project for optimizing marketing mudget allocation using Python.

2.Covers Linear and Non-Linear modeling approaches.

3.Includes completely solved jupyter notebooks, including budget optimization code that you can reuse - Predict Rating given Amazon Product Reviews using

NLP Sessions: 25 1hr 58m1.Learn how to use Python to predict ratings given Amazon product text reviews.

2.Covers the foundational NLP concepts with intuition, theory and code demo.

3.Practice using Python packages such as nltk, gensim, re, sklearn for various NLP tasks.

- Spacy for NLP Sessions: 66 4hr 29m
Master Industry level natural language processing using spacy

- Base R Programming Sessions: 79 6hr 50m
Get started with R-Programming with 9+ hours of in-depth content. Great for beginners and for data scientists trying to learn R as an added skill.

- Dplyr for data wrangling Sessions: 14 38m
Learn how to write codes and manipulate data using the Dplyr Package in R programming.

- Wrangling data with Data Table Sessions: 16 52m
Learn how to wrangle data using Data Table in R programming language.

- GGPlot2 visualization for data analysis Sessions: 27 1hr 17m
Learn to create and customize different types of visualizations in R programming language using GGPlot2.

- Statistical Foundations for ML in R Sessions: 42 3hr 22m
Learn the core concepts of statistics for Data Science and learn how to implement them in R

- Regression Model in R Sessions: 67 5hr 09m
Learn the statistical models Linear and Logistics Regression in R in depth.

Solve 2 industrial projects using regression models in R. - Caret package in R Sessions: 31 2hr 01m
Learn how to streamline the model training process for complex regression and classification problems using Caret package in R

who solved real Industry Projects

Know your coach

Principal Data Scientist

Hi everyone, Iâ€™m Selva Prabhakaran, Your instructor

I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience Iâ€™ve deployed 20+ global products. Iâ€™m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, Iâ€™ve put up the series of courses and projects with detailed explanations â€“ just like an on the job experience. Hope you love it!

Get Data Science Jobs

Deploy your first AI software

Ideate AI based products

Be able to oversee data science projects

Launch AI business

Crack interviews

Data Science aspirants seeking jobs

Data Science practitioners looking to hone skills

Professionals who want to switch to Data Science career

Non-tech managers who want to oversee DS projects

Leaders who to digitally transform their organization

Entrepreneurs wishing to launch a business in AI space

When You Complete This Course, You get certificate for each of the

23 Courses in Machine Learning Plus University.

â€śYou explain things very simple and very clear....â€ť

â€śHis simple way of explaination gave me confidence....â€ť

â€śCourse was made and explained in very simple way....â€ť

The complete machine learning and deep learning path is an absolute no-brainer! Even with zero data science experience, I was able to grasp all the concepts. Helped me big time in my projects.

11:49 am Â· 29 Oct, 2021

In my early days of career, I used ML+ content to gain experience on different concepts and projects. The content over there is easy to understand and also very engaging. Many thanks to the team for providing a platform to play arond with the data.

01:39 pm Â· 12 Dec, 2021

Despite being in this field for few years, the courses add a lot of value for easy understanding of the concepts.Must have for every data scientist who wants to keep growing in this space!

10:56 am Â· 19 Jan, 2022

- Q. Do I need any programming experience before joining Machine Learning Plus University?
- Q. Do I need machine learning experience ?
- Q. What happens after I purchase?
- Q. Do I need any special software or hardware?
- Q. How will I be charged?
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- Q. Do you provide bulk Machine Learning Plus University memberships to business, colleges etc?