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The objective of this Course is to

  • Make a learner ready for solving real life problems using ML
  • Understand all concepts via coding for ML implementation
  • Participate in Kaggle competitions
  • Be ready to learn “Advanced Machine Learning” and “deep learning” in future
  • Code in Python and complete understanding of all ML algorithm’s

Module 1 : Terminology & concepts

  • Why Machine learning and what is it?
  • What is an Error function or loss function like Gradient Descent mean?
  • Some simple real life examples on :
  • Linear regression – Predicting the Price of a House.
  • Logistic regression – Classifying diabetic people from healthy ones.
  • Decision Tree – like Google Play store Recommending Apps to us.
  • Naive Bayes – like detecting Spam mails on Gmail / yahoo.
  • KNN – help Domino’s to open 2 new outlets in your locality.
  • 2 Types of Machine Learning : Supervised & Unsupervised
  • Machine Learning work flow steps.

Module 2 : Python for Data Science

  • NumPy basics for Data Science
  • Pandas for Data Analysis
  • Matplotlib for Data Visualization
  • Scikit-Learn for Data Science

Module 3 : Processing, Wrangling, and Visualizing Data

  • Handling Missing Values
  • Handling Duplicates
  • Encode Categorical
  • Normalizing Numeric Values
  • Data Summarization

Module 4 : Feature Engineering and Selection

  • Feature Engineering Numeric Data
  • Feature Engineering Categorical Data
  • Feature Engineering Text Data
  • Feature Scaling
  • Feature Selection

Module 5 : Machine learning algorithms for supervised and unsupervised learning

— Supervised Algorithms – Maths part + Python Coding

  • Naive Bayes Classification
  • Linear Regression
  • Support Vector Machines
  • Decision Trees
  • Random Forests
  • KNN (K-Nearest Neighbors)

 

— Unsupervised Algorithms –Maths part + Python Coding

  • k-Means Clustering
  • Principal Component Analysis

Module 6 : Applying knowledge to solve real world problems

Project 1: Consumer complaint classification for a Fin-Tech Company

Dataset source: Kaggle

Project 2: Doing Sentiment Analysis of live twitter feeds for any current hot topic

Dataset source: extracted live through twitter API


Dreams Plus an Exin accredited organization for Training, Certification, Courseware in Chennai and in several other places with a professional EXIN certification.

To ensure a practical learning experience for our students, we conduct high-quality training using VMEdu’s online and classroom course material presented in multiple formats such as podcasts, video lecturers, simulated tests and mobile apps.

DreamsPlus an Peoplecert Accredited Organization for Training, Certification, Courseware in Chennai and several other places.

Leading training organisation with PearsonVUE test centre  facility. Our trained students and new students could use the testing facility to deliver more than 200+ It exams.. Pearson VUE — is  the global leader in computer-based testing.

Enjoy  your testing  and training  experience in one place.