Work on real time cloud projects and Embiot projects as their assignments.
Our Data science and machine learning course intends to provide a deep understanding knowledge on the subject, in this programme Embiot Technologies covering Ten modules that has theory and practical approach. Course includes python programming, linear algebra, statistics, error matrix, machine learning and supporting algorithm. Modules are made to understand the building blocks of the data science and machine learning techniques, algorithms with application based hands on sessions.
What is Data Science?
What is Machine Learning?
What is Deep Learning?
What is AI?
Data Conversions
Data Analytics & it's types
What is Python?
Why Python?
Install Python
Python IDES
Jupyter Notebook Overview
Python Basic Data Types
Lists
Slicing
Conditional Statements
Loops
Dictionaries
Tuples
Functions
Array
Selection by position & Labels
Pandas
Numpy
Sci-kit Learn
Matplot Library
Linear Systems
Independent Vectors, Basis
Eigen Values and Eigen Vectors
PSD Matrix
Singular Value Decomposition
Reading CSV Files
Saving in Python Data
Loading Python data objects
Writing data to csv file
Selecting rows/observations
Rounding Numbers
Merging Data
Data aggregation
Data Munging techniques
Probability Basics
Classification
Regression
Linear Regression
Multiple linear Regression
Logistic regression
K-Means
K-Means ++
Hierarchical Clustering
Support Vectors
Hyperplanes
Linear Hyperplane
Linear
Radial
polynomial
K – Nearest Neighbour
Random Forest
Data Preparation
Exploratory Data analysis
polynomial
Model Validation
Model Implementation
Assumptions of PCA
Working Mechanism of PCA
Types of Rotations
Standardization
Positives and Negatives of PCA