Data Analysis

Data Analysis

Machine Learning

Data analysis is a technique within which data is collected and arranged in order that one will derive useful info from it. In different words, the most purpose of data analysis is to seem at what the data is trying to tell us.for instance, what will the data show or do? What will the data not show or do?

You’ll learn how to conduct data science by learning how to analyze data.In this course you will be learn how to import data, analyze it, explore it,learn from it, visualize it and how to easily generate shareable report. Python is a combination of Numpy, Scipy, Pandas and Matplotlib can be used as a replacement for MATLAB.Numpy, Scipy, Pandas, Matplotlib complitly free alternative to MATLAB.

It’s a very powerful programming language, which makes it more flexible,free,portible than Matlab. Most importantly, with SciPy you’re working in Python, which is a fully featured, object-oriented language. Python emphasizes productivity and code readability. Class and function definitions. String manipulation. Great GUI Toolkit etc.

Major advantages of Python

Community Support:

  • -Stackoverflow
  • -Mailing List
  • -User-contributed code and documentation

Usability:

  • -Less Coding
  • -Debugging is easier
  • -Nice Syntax

Flexibility:

    Code Repositories:
  • Pypi is a repository of Python Software and consisting of libraries. Anyone can contribute to Pypi.
Why Data Analysis?

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.SciPy adds even additional MATLAB-like functionalities to Python. Python is rounded get in the direction of MATLAB with the module Matplotlib, that provides MATLAB-like plotting practicality.

Many professionals and student may be confused that what should be use R and MATLAB to solve thier data analysis and data science problems. Which language they shoud be choose.

R is especially used once the data analysis task requir standalone computing or analysis on individual servers.Python is mostly used once the info analysis tasks got to be integrated with net apps or if statistics code must be incorporated into a production information. Python is additionally combination with its specialised modules, like Numpy, Scipy, Matplotlib, Pandas and so on. Python a perfect artificial language for resolution numerical issues.

To conduct data analysis, you will learn a collection of powerful, open-source, tools including:

  • python
  • jupyter notebooks
  • Pandas
  • NumPy
  • Matplotlib
  • scikit learn
  • nltk
Data Analysis

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