Machine Learning Training in Bangalore

Machine Learning  training in Bangalore

Without being explicitly programmed machine learning course provides the computer the ability to learn. Computer Programs development changes when exposed to new data. Python is the most powerful language in the marketplace.

 The objective of the Course:

Holistic understanding of machine learning is the objective of Machine Learning course, covering theory, learn deep learning algorithms using Python.

TARGET AUDIENCE:
  • Data Science professionals
  • Data Scientist
  • Data Analyst
  • Fresher from Mathematics, Stats and Engineering backgrounds
  • Statistician
Machine learning Training in Bangalore

Course Content:

  • Features of python language
  • How python is different from other languages
  • Python installation
  • distribution for Windows, Mac, Linux.
  • python script sample
  • How to work with Python IDE’s.
  • Data types, Variables, Keywords program running using python programming
  • Indentation and Code Comments
  • Names and variables
  • Numeric: int, float, complex – Containers.
  • Basic Operators
  • The Slice Operator [n: m] and slicing
  • if, for, while, range (), break, continue, else
  • access modifiers
  • OOPS paradigm – Inheritance
  • Encapsulation and polymorphism in Python
  • Return Types and parameters
  • connection with Database for pulling data and lambda expressions
  • Open read and write into a File
  • current position resettling in a File
  • The Pickle
  • The Shelve
  • Exception concept
  • An Exception raising
  • An Exception catching
  • Matrices and arrays
  • ND-array object
  • Indexing array
  • Data Types
  • Broadcasting array math
  • standard Deviation
  • Conditional Prob
  • Correlation and covariance
  • Builds on top of NumPy and SciPy cluster
  • Bayes Theorem using SciPy
  • Plotting Line, Pie, Bar, Scatter, Histogram, 3-D
  • Subplots
  • The Matplotlib API
  • NumPy array to a data frame, Data frames
  • Import Data
  • Data operations
  • Introduction to Machine Learning
  • Linear Regression
  • Time Series
  • Natural Language Processing introduction
  • NLP approach for Text Data
  • Jupyter Notebook
  • Sentence Analysis
  • Scikit-Learn of ML algorithms
  • Bag of Words Model
  • Feature Extraction from Text
  • Search Grid
  • Multiple Parameters
  • Build a Pipeline
  • Web Scraping
  • Web Scraping Libraries
  • Installation of libraries
  • Python Parser installation
  • an input HTML using soup object
  • the Soup Tree object navigation
  • Tree searching
  • Print output
  • Partial or full parsing.

APPLY FOR THE COURSE!

image
https://sanitsolutions.in/wp-content/themes/imperio/
https://sanitsolutions.in/
#7dc771
style1
paged
Loading posts...
/home/servecyw/public_html/sanitsolutions.in/
#
on
none
loading
#
Sort Gallery
on
yes
yes
off
Enter your email here
off
off