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Artificial Intelligence

Artificial Intelligence 1

About the Course

Ethans training institute Pune provides you Articial Intelligence training in pune (pimple saudagar and Kharadi area). Our AI Training includes Machine Learning,Deep Learning, Neural Network and Tensor Flow Training

  • Duration: 50 hours class room program, 8 Weekends
  • Prerequisites: Good understanding of Python Programming and package like Numpy, Sklearn, Pandas and Matplotlib (Self Paced Modules and classes are available on request)
  • Lab: Execises on Multiple Algorithims in ML, DL and NN using Python and Tensor Flow

After the classes:

  • Students will Good understanding on Python and AI
  • Deep Learning Concepts are clear and ready towork indivisually

Who gets this training?

  • Robotics Engineer
  • Data Scientist
  • Business Analysts
  • Hadoop Developers
  • Python for Data Science
  • College Graduates



Welcome to the course!

  • Applications of Machine Learning
  • Why Machine Learning is the Future

Data Preprocessing

  • Missing Data
  • Categorical Data
  • Splitting the Dataset into the Training set and Test set
  • Feature Scaling

Using Git and GitHub

  • Setting up Your GitHub Account
  • Configuring Your First Git Repository
  • Making Your First Git Commit
  • Pushing Your First Commit to GitHub
  • Git and GitHub Workflow Step-by-Step


Simple Linear Regression

  • Dataset + Business Problem Description
  • Intuition
  • Simple Linear Regression

Multiple Linear Regression

  • Dataset + Business Problem Description
  • Intuition
  • Multiple Linear Regression

Polynomial Regression

  • Intuition
  • Python Regression Template
  • Polynomial Regression

Support Vector Regression (SVR)

  • Intuition
  • Decision Tree Regression

Decision Tree Regression

  • Intuition
  • Decision Tree Regression

Random Forest Regression

  • Intuition
  • Random Forest Regression

Evaluating Regression Models Performance

  • R-Squared Intuition
  • Adjusted R-Squared Intuition
  • Evaluating Regression Models Performance
  • Interpreting Linear Regression Coefficient


Logistic Regression

  • Intuition
  • Logistic Regression
  • Python Classification Template

K-Nearest Neighbors (K-NN)

  • Intuition
  • K-NN

Support Vector Machine (SVM)

  • Intuition
  • SVM

Decision Tree Classification

  • Intuition
  • Decision Tree Classification

Random Forest Classification

  • Intuition
  • Random Forest Classification

Evaluating Classification Models Performance

  • False Positives & False Negatives
  • Confusion Matrix
  • Accuracy Paradox
  • CAP Curve
  • CAP Curve Analysis

K-Means Clustering

  • K-Means Clustering
  • Intuition
  • Random Initialization Trap
  • Selecting The Number Of Clusters
  • K-Means Clustering

Hierarchical Clustering

  • Intuition
  • Hierarchical Clustering How Dendrograms Work
  • Hierarchical Clustering Using Dendrograms
  • HC

 Natural Language Processing

Deep Learning
Artificial Neural Networks

ANN Intuition

Building an ANN

  • Business Problem Description
  • Building an ANN
  • [Exercise] Should we say goodbye to that customer?

Evaluating, Improving and Tuning the ANN

  • Evaluating the ANN
  • Improving the ANN
  • Tuning the ANN
  • [Exercise] - Put me one step down on the podium

Convolutional Neural Networks

CNN Intuition

Building a CNN

  • Building a CNN
  • [Exercise] - What's that pet?

Evaluating, Improving and Tuning the CNN

  • [Exercise] - Get the gold medal

Dimensionality Reduction

  • Principal Component Analysis (PCA)
  • Linear Discriminant Analysis (LDA)

Model Selection & Boosting
Model Selection

  • k-Fold Cross Validation
  • Grid Search

TensorFlow and Machine Learning

  • Introducing TF
  • Lab: Simple Math Operations
  • Computation Graph
  • Tensors
  • Lab: Tensors
  • Image Processing
  • Images As Tensors
  • Lab: Reading and Working with Images
  • Lab: Image Transformations
  • Introducing MNIST
  • Lab: K-Nearest-Neighbors
  • Individual Neuron
  • Learning Regression
  • Learning XOR
  • XOR Trained

Regression in TensorFlow

  • Lab: Access Data from Yahoo Finance
  • Non TensorFlow Regression
  • Lab: Linear Regression - Setting Up a Baseline
  • Gradient Descent
  • Lab: Linear Regression
  • Lab: Multiple Regression in TensorFlow
  • Logistic Regression Introduced
  • Linear Classification
  • Lab: Logistic Regression - Setting Up a Baseline
  • Logit
  • Softmax
  • Argmax
  • Lab: Logistic Regression
  • Estimators
  • Lab: Linear Regression using Estimators
  • Lab: Logistic Regression using Estimators


  • All State Insurance Claims Severity Prediction
  • Forecast inventory demand based on historical sales data