Python Libraries

Python:-

It is the most popular programming language and it is replace many programming language. Guido Van Rossum created this language in 1991. It is used in web development,software development,mathematical activity.

Python has a many libraries. Many developers are creating python libraries for maching learing. Here is the some python libraries.

How install Python?

1] First you have to install python in your system.For that go to python official website https://www.python.org/

2] Then click on download python. After download click on install.

1] Pandas:

Pandas is an python Library & it is performing operation on data set .It do manipulating, analysing,cleaning data.Pandas is very useful libraries when we are performing anythings data science related in python.

The benefits to use

It is lost of flexible.
It is allow work with large data set.
Data set joining and merging.
Efficient and Fast for manipulating and analyzing data.

How to install pandas?

1] open command prompt and type pip install pandas and press enter then it Successfully installed.

Why Pandas is used for Data Science

Pandas are generally used for data science .The data produced by Pandas are often used as input for plotting functions of Matplotlib, statistical analysis in SciPy, and machine learning algorithms in Scikit-learn. It is built on the top of the NumPy library which means that lot of structures of NumPy are used or replicated in Pandas. .

Features Of Pandas:

Pandas make that the entire process of manipulating data will be easier. Support for operations such Sorting,Re-indexing, Iteration, Aggregations, Concatenations and Visualizations are among the feature highlights of Pandas.

Example:

2] NumPy:

It is the most popular machine learning library in Python. It is stand for Numerical Python.It is the commonly used python library. It is used to perform mathimatical operation.It has in-built mathematical function.TensorFlow also use NumPy to perform some internally operation on tensors.

1]open command prompt and type pip install NumPy and press enter then it Successfully installed.After install then go to IDE and use NumPy typing command Import NumPy as np.

Use of NumPy:-

Bitwise operation
Linear algebra
Matrix operation
Searching,Sorting & Counting
Statistical operation
Stacking

Why Uses Numpy?

NumPy interface can be utilized for expressing images, sound waves, and other binary raw streams as an array of real numbers in N-dimensional.

For implementing NumPy library for machine learning having knowledge of Numpy is important for full stack developers.

Example:

3] Tensorflow:

TensorFlow is a high-performance numerical calculation library that is open source. It is also employed in deep learning algorithms and machine learning algorithms. It was created by the Google Brain team researchers within the Google AI organization and is currently widely utilized by math, physics, and machine learning researchers for complicated mathematical computations. TensorFlow is designed to be fast, and it employs techniques such as XLA.

Features:

Responsive Construct: We can easily visualize each and every part of the graph with TensorFlow, which is not possible with Numpy or SciKit.
Adaptable: One of the most essential Tensorflow features is that it is flexible in its operation related to Machine Learning models, which means that it has modularity and allows you to make sections of it stand alone.
It is Simple to Train Machine Learning Models in TensorFlow: Machine Learning models can be readily trained using TensorFlow on both the CPU and GPU for distributed computing.
Parallel Neural Network Training: TensorFlow allows you to train many neural networks and GPUs at the same time.
Open Source and a large community: Without a doubt, if it was developed by Google, there is already a significant team of software experts working on constant stability improvements. The nicest part about this machine learning library is that it is open-source, which means that anyone with internet access can use it.