International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019 851 ISSN 2229-5518 A Review on Python for Data Science, Machine Learning and IOT P.N.Siva jyothi, Rohita Yamaganti Abstract- Python is an object oriented, scripted and interpreted language for both learning and real world programming. Python is a powerful high-level language created by Guido van Rossum. In this paper, we will provide an introduction to the main Python software tools used for Data science, Machine learning techniques and IOT. Briefly, this paper will first introduce Python as a language, and give introduction about Data science, Machine learning and IOT, and then describe packages that are popular in the Data science and Machine learning communities, such as NumPy, SciPy, TensorFlow, Keras ,Matplotlib etc. From there, we will move to show the importance of python for building IOT applications. We will use different code examples throughout. To aid the learning experience, execute following examples contained in this paper interactively using Jupiter notebooks . Keywords: Machine learning · Data Science · IOT · Tools · Languages · Python Introduction 1.1 Introduction to python Python is a general-purpose, high-level programming language which became popular in the recent times .It allows programmer to write the code in fewerIJSER lines that is not In this paper we wish to give brief possible with other languages. The idea of python in the area of Data important feature in Python science, IOT and Machine learning. programming is it supports multiple Python is known to have an programming paradigms. Python abundance of libraries that assist provides a large set of with data analysis and scientific comprehensive standard library computing. For example, we can which is extensible. The main build python application which features of Python are Simple and helps data analysts to analyze large easy to learn, Freeware and open amounts of data for scientific source, High level , Simple and easy computing. The prerequisites for to learn, Freeware and open source, this paper are basic under-standing High level programming language, of statistics, as well as some Platform independent, Portability, experience in any C-style language. Dynamically typed, Both procedure Some knowledge of Python is useful oriented and Object oriented, but not a must. Interpreted, Extensible, Embedded, Extensive Library. An accompanying Github repository is provided to aid the tutorial. It contains a number of notebooks of IJSER © 2019 http://www.ijser.org International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019 852 ISSN 2229-5518 python code snippets for reference. uncertainty. Python provides It helps to go through number of various predefined modules to work examples related to different on Data science projects. modules of Python. 1.3 Introduction to Machine Https://github.com/mdbloice/MLDS Learning The term machine learning refers to the automated detection of meaningful patterns in data. In the past couple of decades it has become a common tool in almost any task that requires information extraction from large data sets. We are surrounded by a machine learning based technology: search engines 1.2 Introduction to Data Science learn how to bring us the best Data science is a multi- results (while placing profitable disciplinary area that uses scientific ads), anti-spam software learns to methods, procedures, tools and filter our email messages, and credit systems to extract knowledge and card transactions are secured by get insights into structured and software that learns how to detect unstructured data. Data science is frauds. Digital cameras learn to related to data analytics, data detect faces and intelligent personal mining and big data. It understands assistance applications on smart- the phenomenon of the data. It phones learn to recognize voice employs techniquesIJSER and theories commands. drawn from many fields within the Cars are equipped with context of mathematics, statistics, accident prevention systems that are computer science, and information built using machine learning science. algorithms. Machine learning is also widely used in scientific applications such as bioinformatics, medicine, and astronomy. One common feature of all of these applications is that, in contrast to more traditional uses of computers, in these cases, due to the complexity of the patterns that need to be detected, a human programmer Statistics is one of the most cannot provide an explicit, fine- important disciplines to provide detailed specification of how such tools and methods to find structure tasks should be executed. Taking in and to give deeper insight into example from intelligent beings, data, and the most important many of our skills are acquired or discipline to analyze and quantify refined through learning from our IJSER © 2019 http://www.ijser.org International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019 853 ISSN 2229-5518 experience (rather than following electromechanical systems (MEMS) explicit instructions given to us). and the internet. Machine learning tools are concerned with endowing programs with the ability to “learn “and adapt. As per the TIOBE index, Python was the programming language of the year in 2018. With a Because machine learning is rating of 10.020%, it is also the 3rd typically used to process large most popular language in volumes of data, you may want to 2019.Python is mostly used for choose a powerful low-level writing web applications, but it has language. However, if you’re only gained popularity in the IOT just beginning to explore this field, it system. It is an interpreted language might be better to start with Python. that offers readability with syntax Python is beginner-friendly, and can without compromising the size. This do the same thing that other coding language has a large number of languages can, but in fewer lines of libraries; it can get more stuff done code.If you are interested in with fewer codes. Python’s clean exploring machineIJSER learning with syntax is suitable for database Python, this paper will serve as your arrangement. In case your app guide. This is paper gives overview needs the data to be arranged in a of programming machine learning database format or use tables. using Python. Python is the right choice available. Python is the right choice, for data 1.3 Introduction to IOT analysis in IOT systems. The language is simple and can be easily The Internet of Things deployed. Its large community helps (IOT) is a scenario in which objects, in providing help and libraries as animals or people are provided with and when required. It is the ideal single identifiers and the capability language for data-intensive to automatically transfer and the applications. capability to automatically transfer data more to a network without 2. Objectives of Study requiring human-to-human or human-To-computer 1. To conceptualize the features of communication. IOT has evolved Python from the meeting of wireless 2. To investigate python modules Technologies, micro- for Data Science like Numpy IJSER © 2019 http://www.ijser.org International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019 854 ISSN 2229-5518 which is used for matrix and development of a wide range of vector manipulation,Scipy, the applications from simple text 2D plotting library Matplotlib etc processing to WWW browsers to 3. To focus on python modules for games. Machine learning like Tensor flow numerical computations for machine learning, Keras for neural networks and deep learning Each will be discussed in this paper. 3. Related Works 3.1 Basic Features of Python Python is a general-purpose interpreted, interactive, object- oriented, and high-level programming language. It was created by Guido van Rossum 3.2 Python for Data Science during 1985- 1990. Like Perl, Python source code is also These are the most essential Data available under the GNU General Science libraries you have to Public License (GPL). This paper know: gives enough understanding on Python programming language. Numpy IJSER Matplotlib Python is Interpreted − Scipy Python is processed at runtime by the interpreter. You do not need to Numpy: Numpy will help us to compile your program before manage multi-dimensional arrays executing it. This is similar to PERL very efficiently. Maybe it is difficult and PHP. to do that directly, but since the Python is Interactive − you concept is a crucial part of data can actually sit at a Python prompt science, many other libraries (well, and interact with the interpreter almost all of them) are built on directly to write your programs. Numpy. Simply to say, without Python is Object-Oriented − Numpy it is difficult to use Pandas, Python supports Object-Oriented style or technique of programming that encapsulates code within objects. Python is a Beginner's Language − Python is a great language for the beginner-level programmers and supports the IJSER © 2019 http://www.ijser.org International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019 855 ISSN 2229-5518 Matplotlib, Scipy or Scikit-Learn. usually it provides many functions like barchart,scatterplot,piechart,histogr am etc which are useful for projecting many dimensions of data. 3-dimensional Numpy array: But on the other hand, it also has a few well-implemented methods. It’s quite to use Numpy random function, which is found slightly better than the random module of the standard library. And when it Scipy: comes to simple predictive analytics tasks like linear or polynomial Mathematics deals with a huge regression, Numpy polyfit function number of concepts that are very will be favorite. important but at the same time, complex and time-consuming. However, Python provides the full- fledged scipy library that resolves IJSERthis issue for us. In this scipy, we will be learning how to make use of this library along with a few functions and their examples.