Machine Learning in Python

Open the doors to a very exciting and most popular fields of Machine Learning.

₹27,150.00 ($333.24)

About Our Course:

This course will introduce you to a very exciting and highly popular Machine Learning. You'll get applied experience in major areas of Machine Learning which include Prediction, Classification, Clustering and Information Retrieval. Learn to analyze large & complex datasets, build systems that adapt and improve over a period of time, and develop smart applications to make predictions from data.

Machine Learning in Python Thumbnail
Machine Learning in Python
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
  • Lecture 6 Lectures
  • Course Walkthrough Preview
  • Overview to Machine Learning Preview
  • Artificial Intelligence Vs Machine Learning Vs Deep Learning
  • Machine Learning: Python Libraries
  • Supervised Vs. Unsupervised Learning
  • Module Quiz: Machine Learning Overview
  • Lecture 12 Lectures
  • 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
  • Demo Machine Code: Linear Regression using SKLEARN Coding
  • 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
  • Lecture 8 Lectures
  • 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
  • Lecture 4 Lectures
  • Clustering Algorithms in Machine Learning
  • Clustering Vs Classifications: Machine Learning
  • K means Clustering - Introduction
  • Module Quiz: Clusterin in Machine Learning
  • Lecture 4 Lectures
  • Understanding Recommender Systems in Machine Learning
  • Content-based Filtering: Recommendation Systems
  • Collaborative Filtering: Recommendation Systems
  • Module Quiz: Recommender Systems in Machine Learning
  • Lecture 3 Lectures
  • Introduction to the Project: Guess Game
  • Project Implementation: Undestanding the Concepts to Build Guess Game
  • Proejct Code: Guess Game Using Python
  • Lecture 4 Lectures
  • Understanding Python Libraries
  • Three-dimensional Plotting in Python using Matplotlib
  • Tri-Surface Plot in Python using Matplotlib
  • Professional 3D Plotting in Matplotlib - 3D Plot Game
  • Lecture 6 Lectures
  • Understanding Machine Learning Concepts
  • Flowcharts - Problem Solving with Python
  • Deep Learning: Training and Testing the Network with Tensorflow and Keras
  • Tensorflow and Keras For Neural Networks and Deep Learning
  • Final Certification Quiz; Complete Course
  • Machine Learning Final Assignment
  • Lecture 1 Lectures
  • Machine Learning Live Class with Google Expert
  • Lecture 4 Lectures
  • Logistic Regression for Malignancy Prediction in Cancer (Breast Cancer)
  • Spam Mail Prediction using Machine Learning with Python
  • Personal Assistant
  • Weather recommendation system
  • Lecture 7 Lectures
  • 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
  • Lecture 1 Lectures
  • Hands-On-Guide To Machine Learning Model Deployment Using Flask
  • Lecture 1 Lectures
  • GitHub Tutorial and Profile Buidling
Our Mentors:
Jyoti Sharma

Jyoti Sharma

OK Google Developer

4.6 Rating

Sample Certificate:
What Jyoti Sharma has to say:

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. Happy learning to all the students!

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Any student can pass the Perfect eLearning scholarship test and avail the Learn Now, Pay Later facility.

Success Stories

The words of these guys are pure pleasure.

Thank you Perfect eLearning for such informative course. The learning material, practical knowledge and technical expertise helped me grab the job. I would like to thank the entire team at Perfect Plan B for empowering me.
Every accomplishment start with the decision to try. Taking the course at Perfect eLearning is one of the crucial decision I have made and Perfect eLearning made it as the best. Thank you Perfect eLearning to help me to grab ...
I got 45% hike after doing the MACHINE LEARNING Course. Perfect eLearning officially inspired me learn more and more. Now I have the skill set that is required by today's industries, with ample of oppertunities in front of me.
Perfect eLearning helped me to learn the technologies from scratch which game me strong command in building applications using the latest technologies. Finally I fulfilled my dream with the help of Perfect elearning
I just want to say Thank you all for being so helpful supportive and friendly throughout this placement. I really had a fantastic time and learnt so much along the way. The things that I have learnt will be invaluable to my future placement...
My name is Ramya Pokala.I got placed in VLink.I just want to Thank you all for your support and guidance throughout this placement.Before joining in Perfect eLearning I really have zero knowledge on python and machine learning but afte...