Machine Learning in Python
Studying machine learning opens world of opportunities to develop cutting edge machine learning applications in various verticals. Around 84.4% of professionals mentioned that recruiters look for Machine Learning as the most crucial skill when hiring a Data Scientist.-
Refer & Earn
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4.8/5 (234)
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4.8/5 (234)
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4.8/5 (234)
Who should enroll in Machine Learning in Python?
Python developer, Machine Learning Engineer, Data Scientist, NLP Scientist, Business Intelligence Developer, or a Human-Centred Machine Learning Designer.
Why Should You Learn This course?
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Beginner Friendly
Concise and easy to understand syntax -
Versatile
Over 125,000 Libraries available -
In High-Demand
Fastest growing Programming Language
Hiring Company
What you will learn
- Introduction to Machine Learning
- Artificial Intelligence vs Machine Learning
- Linear Regression using Python
- Multiple Linear Regression
- Evaluation Metrics For Classification
- Machine Learning random forest algorithm
- Clustering algorithms in Machine Learning
- Clustering vs Classification
- Recommender system in Machine Learning
- Machine Learning Projects
- Decoding Model selection for Machine Learning
- Machine Learning Model Deployment using Flask
Technologies you'll Master
We have designed this course as per the Industry requirements. In this course, you will gain practical experience and learn various tools based on the most recent technologies, such as: Numpy, Seaborn, Pandas, Matplotlib, TensorFlow, Flask and much more….
Project
Breast Cancer Prediction
This project aimed to predict breast cancer using different machine-learning approaches.
Weather Recommendation system
This project takes parameters such as temperature, humidity, and wind to forecast weather.
Movie recommendations system
This project use a set of different strategies and algorithms to help users find the most relevant films.
Medical cost prediction
This project will apply Machine Learning algorithm and Linear Regression to predict Healthcare Insurance costs.
Face Mask Detection
This project refers to detect whether a person is wearing a mask or not.
Deep learning project with Tensorflow
In this project we will use tensorflow framework created by Google for creating Deep Learning models.
Python Plagiarism Checker
In this project we build our own plagiarism checker to search vast database for stolen content.
Chatbot AI
In this Project we build a chatbot program that simulates human conversation or "chatter" through text or voice interactions.
Course Journey
Phase 1
Video Lectures & Live Classes
Dive into 100+ video lectures to build strong foundation starting from the very basics to advanced levels. 24/7 learning support from industry experts to clear up any conceptual doubts.Phase 2
Focus on projects
Capstone projects using real-world data sets with virtual labs for practical training.
Phase 3
Resume building, Mock interviews
Learn to make ATS-proof Latex Resume to get in eyes of the Recruiter easily. Get trained by experts, clear mock tests and Comp-coding rounds to get ready for Interviews.Phase 4
Internship & Placement
Get the required pre job experience to make your profile stand out. Make your dream of working in the tech company of your choices true with 100% assured placements.
Program outcomes
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In-depth knowledge in data analytics and data Visualisation. - Good Command over Data Structure and algorithms, Machine learning,web scraping, and natural language processing.
- Mastery in essential concepts of data types, tuples, lists, dicts, basic operators, and functions.
- Hands on experience on Various live Projects.
- ATS Proof Latex Resume building and career-ready Skills.
Who will teach?
Jyoti Sharma
4.4 ReviewsOK Google Developer
B.Tech & M.Tech Computer Science at NIT Kurukshetra (Department Ranker 1, CGPA: 9.8) with experience in Android App Development and Machine Learning. I am highly enthusiastic about learning and teaching cutting-edge technologies. My interests include Teaching, Data Structures, Algorithms, and Problem Solving. Worked at Infoedge(Naukri), Ok Google, and got offers from various tech companies including Adobe, UrbanCompany, etc, I would love to create more developers by imparting what I know.
13 Topic
- Machine Learning Introduction
- Regression in Python
- Introduction to Regression
- Various Regression Techniques: Linear, Polynomial, Stepwise, Ridge, Lasso and ElasticNet
- Linear Regression using Python
- Linear Regression Techniques: Slopes And Intercept
- Linear Regression using SKLEARN Coding
- Linear Regression Demo using Scikit Lean Code Link
- Demo Code Explaination: Linear Regression using SKLEARN Coding
- Errors in Linear Techniques
- R-Squared or Coefficient of Determination
- Multiple Linear Regression (MLR)
- Polynomial Vs. Non Linear Regression
- Module Quiz: Regression in Python
- Machine Learning with Python: Classification
- Introduction to Classification
- K-Nearest Neighbor(KNN) Algorithm for Machine Learning Introduction
- Working with K-Nearest Neighbor(KNN) Algorithm for Machine Learning
- Evaluation Metrics for Classification
- Machine Learning Decision Tree Classification Algorithm
- Support Vector Machine (SVM) Algorithm in Machine Learning
- Machine Learning Random Forest Algorithm
- Module Quiz: Classification
- Clustering or Cluster Analysis in Machine Learning
- Recommender Systems in Machine Learning
- Python Project 1( Beginner Level): Building Your Own Guess Game
- Python Project 2 ( Intermediate Level): Playing with Graphs (Data Science Project)
- Python Project 3 (Advanced Level): Machine Learning (Deep Learning Project With Tensorflow)
- Live Class: Machine Learning
- Python Capstone Projects
- Machine Learning Workflow Optimization Techniques
- Understanding Machine Learning Workflow
- Decoding Model Selection for Machine Learning
- Understanding Overfitting in Machine Learning
- Understanding Underfitting in Machine Learning
- Understanding the Bias-Variance Tradeoff
- Introduction to Dimensionality Reduction for Machine Learning
- Gradient Descent algorithm and its Variants
- Machine Learning Model Deployment
- Developer Showcase: GitHub
Online
06/02/2023 - 06/05/2023 
12.00 AM - 2.00 PM (IST) Weekned
