Machine Learning

Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding those data and information in the form of observations and real-world interactions. The first and most important thing we focused on is giving the course a robust structure. Machine Learning is very broad and complex and to navigate this maze you need a clear and global vision of it. Every practical tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means. Technoxian offers you a creative platform to magnify your skill set and potential through Workshops on 'Machine Learning' under the guidance of Industry-best experts. The Workshop gives you a Real-Time exposure to this future technology.

Workshop Highlight

  • Exposure with Industry Experts.
  • Hands on Practice.
  • Certificate of Participation by All India Council for Robotics & Automation
  • Free AICRA student membership.

Introduction to Machine Learning

  • What is Machine Learning?
  • Applications
  • Objectives
  • Industrial Needs
  • Tool-kits

Data Manipulation and Visualization

  • What is Numpy?
  • Ndarray Object
  • Array Attributes and Manipulation in Numpy
  • Indexing & Slicing
  • Reshaping
  • Introduction to Pandas
  • Series and DataFrame in Pandas
  • Basic Functions in Pandas
  • Indexing and Selecting Data
  • Missing Data
  • Categorical Data
  • 2D Plotting with matplotlib
  • Plotting with keyword strings
  • Plotting with categorical variables
  • Analyzing data with seaborn

Machine Learning Algorithms

  • Supervised Learning Algorithms
  • Simple Linear Regression
  • Multiple Linear Regression
  • Support Vector Regression
  • Decision Tree Regression
  • Random Forest Regression
  • Support Vector Classification(SVM)
  • K - Nearest Neighbors Algorithm(KNN)
  • Naive Bayes Classification
  • Decision Tree Classification
  • Random Forest Classification
  • Unsupervised Learning Algorithms
  • Elbow Method
  • K-means clustering
  • Dendograms
  • Hierarchical clustering
  • Dimensionality Reduction
  • Principle component Analysis
  • Linear Discriminant analysis

Model Improvement

  • Gradient Descent
  • Cost Function
  • Regularization Techniques
  • Errors
  • Over fitting and under fitting
  • L1 and L2 Regularization
  • Bias Variance Trade-Off
  • Ordinary Least Squares
  • Mean Squared Error
  • Mean Absolute Error
  • K-Fold Cross Validation
  • Gradient Descent
  • Stochastic Gradient Descent
  • Dimensionality Reduction

Venue: Thyagaraj Sports Complex, New Delhi.

Duration: 10:30 am - 6:30 pm

Participants Strength: 100 Nos.

Registration Fee:

  • For Indian resident: INR 2000/-
  • For [ Non India ] resident: USD 30 (including GST)

Registration mode: Online

Accommodation: Oyo rooms on 1st come, 1st serve basis. Tariff between INR 500 to 1000 per participant per night.

For any query, call +91 7834-9999-25 or mail us at "info@technoxian.com"

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New-Delhi, 110020

Mobile : +91-7834999925

Email: info@technoxian.com