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  • Data Science & Machine Learning Course Fees: Rs. 18999/-
  • Data Science & Machine Learning Course Duration: 4 months
  • UKIQ Certificate
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Data Science & Machine Learning

Course Highlights

  • Introduction to Data Science
  • Python with Data Science
  • Matplotlib Module
  • Scipy
  • Scikit
  • Machine Learning
  • Data Science & Machine Learning
  • understanding Machine Learning
  • Theano
  • Trensorflow
  • Importance
  • Artificial intelligence

Data Science & Machine Learning Course Details

1) Matplotlib Module

  • Introducation
  • Environment Setup
  • Anaconda Distribution
  • Juypter Notebook
  • Pyplot API
  • Simple Plot
  • PyLab Module
  • Axes Class
  • Figure Class
  • Multiplots
  • Subplots() Function
  • Subplot2grid() Function
  • Grids
  • Formatting Axes
  • Twin Axes
  • Bar Plot
  • Histogram
  • Pie Chart
  • Scatter Plot
  • Contour Plot
  • Quiver Plot
  • Box Plot
  • Violin Plot
  • 3-dimensional Plotting
  • 3D Contour Plot
  • 3D Wireframe Plot
  • 3D Surface Plot
  • Working With Text
  • Mathematical Expressions
  • Working with Images
  • Transforms.

2) Scipy

  • Introducation
  • Environment Setup
  • Basic Functionality
  • Cluster
  • Constants
  • FFT pack
  • Integrate
  • Interpolate
  • Input and Output
  • Linalg
  • Ndimage
  • Optimize
  • Stats
  • CSGraph
  • Spatial
  • ODR
  • Special Package
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3) Scikit
  • Introducation
  • Modelling Process
  • Data Representation
  • Estimator API
  • Conventions
  • Linear Modeling
  • Extended Linear Modeling
  • Grandient Descent
  • Support Vector Machine
  • Anomaly Detection
  • K-MearestNeighbours
  • KNN Learning
  • Classification with Naïve Bayes
  • Decision Trees
  • Rendomized Decision Trees
  • Boosting Methods
  • Clustering Methods
  • Clustering Performance Evaluation
  • Dimensionality Reduction using PCA
4) Theano
  • Introducation
  • Installation
  • A Trivial Theano Expression
  • Expression for matrix Multiplication
  • Computational Graph
  • Data types
  • Variables
  • Shared Variables
  • Functions
7) Trensorflow
  • Introducation
  • Installation
  • Understanding Artificial Intelligence
  • Mathematical Foundations
  • Machine Learning Learning& Deep Learning
  • TensorFlow Basics
  • Convolutional Neural Networks
  • Recurrent Neual Networks
  • TensorBoard Visualization
  • TensorFlow- WordEmbedding
  • Single Layer Perceptron
  • Linear Regression
  • TFLearn and its installation
  • CNN and RNN Difference
  • Keras
  • Distributed Computing
  • Exporting, Multi-Layer Perceptron Learing
  • Hidden Layers of Perceptron
  • Optimizers
  • XOR Implementation
  • Gradient Descent Optimization
  • Forming Graphs
  • Image Recongnition using TensorFlow

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Mentoring By Experts

Flexible Schedule

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Learn By Doing

Goal Oriented