Machine Learning Training

by Esquare Infotech Claim Listing

At the Completion on said course, the students will have full professional knowledge of coding skills, developing logics & websites/applications, and working on live projects. We are the best providers of Python Training in Navi Mumbai, Kharghar with excellent placements. 

₹25000

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Esquare Infotech Logo

img Duration

45 Days

Course Details

At the Completion on said course, the students will have full professional knowledge of coding skills, developing logics & websites/applications, and working on live projects. We are the best providers of Python Training in Navi Mumbai, Kharghar with excellent placements. 

By giving the perfect Python Training in Navi Mumbai, we differ very much from others. By expert guidance in learning Python Training in Navi Mumbai, we can proudly say we are the top providers.

Enroll yourself for a Python course or Python classes in Kharghar Near by following areas are Panvel, Belapur, Kamothe, Nerul, and Vashi in Navi Mumbai.

 

Target Audience:

10th & 12th class students Undergraduates, Graduates Post-Graduates & Job aspirants.

 

Course Content:

  • Introduction: What is Machine Learning? What is Artificial Intelligence?
  • Landscape of problems
  • Supervised versus unsupervised learning
  • Classification versus forecasting
  • Classifying data sets: Tall, wide, and dense data
  • Predictive modeling/ policy intervention
  • Python basics
  • Anaconda
  • Spyder
  • Numpy, Scipy
  • Matplotlib
  • Scikit Learn
  • Model complexity
  • Overfitting
  • Training/validation/testing
  • Simplest models
  • Getting started with scikit-Learn
  • K nearest neighbors
  • Application: Iris data
  • Linear regression
  • Controlling model complexity
  • Regularization
  • Ridge regression
  • Lasso regression
  • Classification
  • Logistic regression
  • Support vectors
  • Naive Bayes
  • Linear discriminant
  • Multi(k>2) class problems
  • Decision trees
  • Controlling complexity again
  • Feature importance and reading trees
  • Bagging predictors
  • Multiple trees (The Random Forest)
  • Boosting
  • Recommendation systems
  • Content based recommendation
  • Collaborative filtering
  • Clustering
  • K-means and Hierarchical clustering
  • Principal component analysis
  • Model evaluation
  • Cross validation
  • Evaluation metrics
  • Tuning Models
  • Navi Mumbai Branch

    45, Bhoomi heights, Sector 8, plot No-5 & 6, Navi Mumbai

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