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Data Science & ML Course

 
Module 1: INTRODUCTION TO NUMPY

What is Numpy?
Basic Mathematics
Creating Numpy arrays from Python structures
Slicing arrays
Using Boolean masking and broadcasting techniques
joining and splitting arrays
Rearranging array elements
Creating universal functions
Finding patterns
Building magic squares and magic cubes with Numpy and Python

Module 2: MATHEMATICS

Scalars, Vectors, Matrices
Tensors, Hyperplanes, Matrix Products
Standard Deviation
Gradient descent and Cost function
Hypothesis function

Module 3: NUMPY: BASIC STATISTICS

Probability and Conditional Probabilities
Posterior Probability
Distributions
Samples vs Population
Resampling Methods
Selection Bias
Likelihood

Module 4: INTRODUCTION TO PRE PROCESSING DATA

Fact and dimention analysis
Dimentionally reduction
Principal component analysis
Feature selection
Feature scaling

Module 5: INTRODUCTION TO PANDAS

Overview of the pandas Series
Look ups, Selections & Indexing
Advanced Indexing Options
Handling NaN Values, Reindexing
Filling Methods and Series Addition
Series Multiplication, More Reindexing & Mapping

Module 6: PANDAS: DATA-FRAMES

DataFrame Basics
Reading Files, Plotting & Basic Methods
More Plotting, Joins, Basic DateTime Indexing & Writing to Files
Adding & Reseting Columns, Mapping with Functions
More mapping, Filling NaN values, Plotting, Correlations & Histgrams
More Plotting, Rolling Calculations, Basic Date Time Indexing
Analysis Concept, Filling NaN Values, Cumulative Sums &Value Counts
Data Maintenance, Adding/ Removing Columns and Rows
Basic Grouping, Concepts of Aggregate Functions

Module 7: INTRODUCTION TO MATPLOTLIB

Different types of basic Matplotlib charts
Labels, titles and window buttons
Legends, Bar Charts, Histograms, Stack Plots, Pie Chart
Loading data from a CSV &NumPy

BASIC CUSTOMIZATION OPTIONS

  • Plotting basic stock data
  • Styles with Matplotlib
  • Creating moving averages with our data*
  • Adding a High minus low indicator to graph*
  • Customizing the dates that show*
  • Label and Tick customizations
  • Customizing Legends
Module 8: OPENCV: IMAGE PROCESSING

What is OpenCV?
Overview of OpenCV, Version and why use OpenCV?
Install OpenCV-Python in Windows OR Linux
Using Python and writing A Program
Installing Python and Writing A Program
Writing the " Hello World " Assignments
Quiz, questions and queries

Module 9: PLAYING WITH IMAGES OR VIDEOS USING OPENCV

Display and Write an image
Capture Video from Camera
Accessing and Modifying pixel values
Accessing Image Properties
Splitting and Merging Image Channels
Image ROI

Module 10: FEATURE DETECTION AND DESCRIPTION

Understanding Features
Harris Corner Detection
Face Detection using Haar-Cascades

PREREQUISITES

None.

Fees: 21999 Rs/-
Duration: 3 Months

Module 1: MACHINE LEARNING ALGORITHMS
Supervised Learning - (Deep Learning)
  • Regession
  • Naive Bayes - Probabilistic Classifier
  • K-Nearest Neighbours - Non-Probabilistic Classifier
  • Support Vector Machines (SVM)
 
Module 2: LINEAR & LOGISTIC REGRESSION

Understanding the context of Regression
Type of Regression

  • Linear Regression
  • Logistic Regression
  • Multiple Regression

Model evaluation:

  • Regression standard error
  • R-squared
  • Testing the slope

Regression model to estimate and predict values
Selecting the best regression equation

Module 3: K-NEAREST NEIGHBOURS - NON-PROBABILISTIC CLASSIFIER

What is KNN classifier?
Calculate K in KNN?
Kind of problem instance in KNN
Difference between Naive Bayes & KNN
Data reduction & Dimensionality Reduction?
Feature extraction in KNN

Module 4: SUPPORT VECTOR MACHINES (SVM)

Learn the simple intuition behind Support Vector Machines.
Implement an SVM classifier in SKLearn/scikit-learn
Choose the right kernel for your SVM
Learn about RBF and Linear Kernels

Module 5: UNSUPERVISED LEARNING - CLUSTERING (INTRODUCTION)

What is unsupervised Learning?
Real-Life use case of clustering in facebook

  • K-Means Clustering
  • Hierarchical clustering
  • Density-Based clustering
  • Distribution-Based clustering
PREREQUISITES

None.

Fees: 21999 Rs/-
Duration: 3 Months

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  • Email: (Delhi) contact@mappingminds.org, (Noida) info@mappingminds.org

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