Rishab - Machine learning tutor - Chennai
Rishab - Machine learning tutor - Chennai

Rishab profile and its contact details have been verified by our team.

Rishab

  • Rate $13
  • Response 3h
  • Students

    Number of students Rishab has accompanied since arriving at Superprof

    50+

    Number of students Rishab has accompanied since arriving at Superprof

Rishab - Machine learning tutor - Chennai
  • 5 (8 reviews)

$13/h

Contact
  • Machine learning

Master Practical Machine Learning and AI from basic Supervised & Unsupervised Learning, to advanced Neural Networks, and Data Science Concepts for Real-World Problem Solving!

  • Machine learning

Lesson location

Super Prof

Rishab is one of our best Machine learning tutors. High-quality profile and excellent qualifications, organised and responsive to lesson requests, appreciated by their students!

About Rishab

I'm a computer science undergrad. I started my coding career when I was 12! Age is not a barrier for gaining knowledge, that's what I believe. I learned AI-ML concepts in just 2 months! You too can do so, just join me!!

See more

About the lesson

  • Elementary School
  • Middle School
  • High School
  • +17
  • levels :

    Elementary School

    Middle School

    High School

    Première

    Terminale

    College

    University

    Adult Education

    Facultate (Licență)

    Masters/ Graduate School

    Doctorate

    Other

    MBA

    Early childhood education

    Beginner

    Intermediate

    Advanced

    Proficient

    Autres

    Children

  • English

All languages in which the lesson is available :

English

1. Introduction to Artificial Intelligence and Machine Learning
1.1. Overview of AI & ML
• What is AI? Types of AI: Narrow vs. General AI.
• The evolution of Machine Learning.
• Key concepts in AI: Intelligent agents, search, problem-solving.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
1.2. Types of Machine Learning
• Supervised Learning: Definition, Use cases.
• Unsupervised Learning: Clustering and association.
• Reinforcement Learning: Introduction and use cases.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
1.3. Setting up the Python Environment
• Installing libraries: NumPy, Pandas, Matplotlib, Scikit-learn.
• Introduction to Jupyter Notebooks & Google Colab.
______________________________________
2. Data Preprocessing and Feature Engineering
2.1. Data Cleaning & Transformation
• Handling missing data, data imputation techniques.
• Encoding categorical data, scaling features.
• Feature extraction and selection techniques.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
2.2. Data Visualization
• Visualizing data using Matplotlib, Seaborn.
• Exploratory Data Analysis (EDA) best practices.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
2.3. Case Study: EDA on a real-world dataset.
______________________________________
3. Supervised Learning Techniques
3.1. Regression Models
• Linear Regression: Theory, implementation, evaluation metrics.
• Polynomial Regression, Ridge, and Lasso Regression.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
3.2. Classification Models
• Logistic Regression, K-Nearest Neighbors (KNN).
• Decision Trees, Random Forests, Support Vector Machines (SVM).
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
3.3. Model Evaluation
• Cross-validation, bias-variance tradeoff.
• Metrics: Accuracy, Precision, Recall, F1-score, ROC, and AUC.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
3.4. Case Study: Building a classifier for real-world data
• Example: Loan approval, image classification.
______________________________________
4. Unsupervised Learning and Clustering
4.1. Clustering Algorithms
• K-means Clustering, DBSCAN, Hierarchical Clustering.
• Dimensionality Reduction: PCA (Principal Component Analysis), t-SNE.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
4.2. Association Algorithms
• Apriori, Eclat for market basket analysis.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
4.3. Case Study: Building a customer segmentation model.
______________________________________
5. Deep Learning and Neural Networks
5.1. Introduction to Neural Networks
• Neurons and layers, activation functions (Sigmoid, ReLU, Softmax).
• Forward and backward propagation.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
5.2. Deep Learning Models
• Convolutional Neural Networks (CNN) for computer vision.
• Recurrent Neural Networks (RNN) for time series and NLP.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
5.3. Deep Learning Frameworks: Keras
• Implementing a basic neural network with Keras.
• Model optimization: Adam, SGD, and learning rate tuning.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
5.4. Case Study: Image classification with CNNs, time-series forecasting with RNNs.
______________________________________
6. Advanced Topics in Machine Learning
6.1. Reinforcement Learning
• Introduction to Q-Learning, policy gradients, and Markov Decision Processes (MDPs).
• Applications in game playing (e.g., AlphaGo).
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
6.2. Transfer Learning
• Using pre-trained models in deep learning (e.g., VGG, ResNet).
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
6.3. Natural Language Processing (NLP)
• Tokenization, Text preprocessing.
• Bag-of-Words, Word2Vec, and Transformers.
• Implementing a basic sentiment analysis model.
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
6.4. Generative Models
• GANs (Generative Adversarial Networks).
• Variational Autoencoders (VAEs).
°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°°
6.5. Case Study: Building an AI agent using reinforcement learning.
______________________________________

See more

Rates

Rate

  • $13

Pack rates

  • 5 h: $65
  • 10 h: $130

online

  • $13/h

Other tutors in Machine learning

  • Arash

    Montreal & online

    5 (17 reviews)
    • $80/h
  • Ali

    Toronto & online

    5 (13 reviews)
    • $45/h
    • 1st lesson free
  • Moe

    Edmonton & online

    5 (11 reviews)
    • $40/h
    • 1st lesson free
  • Ammar

    Montréal

    5 (15 reviews)
    • $25/h
    • 1st lesson free
  • Pedram

    Burnaby & online

    5 (16 reviews)
    • $85/h
    • 1st lesson free
  • Farhad

    Vancouver & online

    5 (14 reviews)
    • $79/h
  • Nishant

    Langley Township & online

    5 (8 reviews)
    • $25/h
    • 1st lesson free
  • Ryan

    Victoria & online

    4.9 (5 reviews)
    • $70/h
  • Mobina

    Vancouver & online

    5 (17 reviews)
    • $70/h
  • Qasim

    Cambridge & online

    4.9 (4 reviews)
    • $35/h
    • 1st lesson free
  • Mehdi

    Vancouver & online

    5 (7 reviews)
    • $33/h
    • 1st lesson free
  • Purva

    Toronto & online

    5 (5 reviews)
    • $26/h
    • 1st lesson free
  • Akshat

    Calgary & online

    5 (2 reviews)
    • $40/h
    • 1st lesson free
  • Vrutti

    Mississauga & online

    5 (4 reviews)
    • $30/h
    • 1st lesson free
  • Sabeera

    Ottawa & online

    5 (28 reviews)
    • $3/h
  • Pankti

    Windsor & online

    5 (4 reviews)
    • $25/h
    • 1st lesson free
  • Anish

    Waterloo & online

    5 (7 reviews)
    • $30/h
    • 1st lesson free
  • Ashita

    Ottawa & online

    5 (3 reviews)
    • $45/h
    • 1st lesson free
  • Simon

    Edmonton & online

    5 (2 reviews)
    • $80/h
  • Ayo

    Toronto & online

    5 (5 reviews)
    • $10/h
  • More Machine learning tutors