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.
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
6 Lectures
- 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
- 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
- 4 Lectures
- Clustering Algorithms in Machine Learning
- Clustering Vs Classifications: Machine Learning
- K means Clustering - Introduction
- Module Quiz: Clusterin in Machine Learning
- 4 Lectures
- Understanding Recommender Systems in Machine Learning
- Content-based Filtering: Recommendation Systems
- Collaborative Filtering: Recommendation Systems
- Module Quiz: Recommender Systems in Machine Learning
- 3 Lectures
- Introduction to the Project: Guess Game
- Project Implementation: Undestanding the Concepts to Build Guess Game
- Proejct Code: Guess Game Using Python
- 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
- 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
- 1 Lectures
- Machine Learning Live Class with Google Expert
- 4 Lectures
- Logistic Regression for Malignancy Prediction in Cancer (Breast Cancer)
- Spam Mail Prediction using Machine Learning with Python
- Personal Assistant
- Weather recommendation system
- 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
- 1 Lectures
- Hands-On-Guide To Machine Learning Model Deployment Using Flask
- 1 Lectures
- GitHub Tutorial and Profile Buidling
Our Mentors:
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!
Hiring Partners
Learn Now Pay later
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.
- Aastha
(Nagarro)
- Anshul
(Accenture)
- Deepak
(Microsoft)
- Pooja
(Sapient)
- Rekha Singh
(Engineer)
- Ramya Pokala
(Trainee Software Engineer)
