Machine Learning Made Easy: A Review of Scikit-learn Package in Python Programming Language

2019 ◽  
Vol 44 (3) ◽  
pp. 348-361 ◽  
Author(s):  
Jiangang Hao ◽  
Tin Kam Ho
Keyword(s):  
Machine Learning ◽  
Programming Languages ◽  
Programming Language ◽  
Data Science ◽  
Machine Learning Algorithms ◽  
The Past ◽  
Machine Learning Methods ◽  
Python Programming Language ◽  
And Behavior ◽  
Python Programming

Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review Scikit-learn, a machine learning package in the Python programming language that is widely used in data science. The Scikit-learn package includes implementations of a comprehensive list of machine learning methods under unified data and modeling procedure conventions, making it a convenient toolkit for educational and behavior statisticians.

Machine learning for the extragalactic astronomy educational manual

2019 ◽  
Vol 15 (S367) ◽  
pp. 461-463
Author(s):  
Maksym Vasylenko ◽  
Daria Dobrycheva
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Programming Language ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Python Programming Language ◽  
Python Programming

AbstractWe evaluated a new approach to the automated morphological classification of large galaxy samples based on the supervised machine learning techniques (Naive Bayes, Random Forest, Support Vector Machine, Logistic Regression, and k-Nearest Neighbours) and Deep Learning using the Python programming language. A representative sample of ∼315000 SDSS DR9 galaxies at z < 0.1 and stellar magnitudes r < 17.7m was considered as a target sample of galaxies with indeterminate morphological types. Classical machine learning methods were used to binary morphologically classification of galaxies into early and late types (96.4% with Support Vector Machine). Deep machine learning methods were used to classify images of galaxies into five visual types (completely rounded, rounded in-between, smooth cigar-shaped, edge-on, and spiral) with the Xception architecture (94% accuracy for four classes and 88% for cigar-like galaxies). These results created a basis for educational manual on the processing of large data sets in the Python programming language, which is intended for students of the Ukrainian universities.

scholarly journals Python for Automating Machine Learning Tasks

2021 ◽  
Vol 2 (2) ◽  
pp. 77-82
Author(s):  
Tinatin Mshvidobadze
Keyword(s):  
Machine Learning ◽  
Programming Language ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Data Breach ◽  
Learning Tasks ◽  
Python Programming Language ◽  
Malicious Insiders ◽  
Python Programming ◽  
Email Filtering

Machine learning is used in a variety of computational tasks where designing and programming explicit algorithms with good performance is not easy. Applications include email filtering, recognition of network intruders or malicious insiders working towards a data breach. In this article we will focus on basics of machine learning, tasks and problems and various machine learning algorithms. The article discusses the Python programming language as the best language for automating machine learning tasks.

Programming Language Support for Implementing Machine Learning Algorithms

2020 ◽  
pp. 402-421
Author(s):  
Anitha Elavarasi S. ◽  
Jayanthi J.
Keyword(s):  
Machine Learning ◽  
Programming Languages ◽  
Programming Language ◽  
Domain Knowledge ◽  
Learning Algorithm ◽  
Mathematical Optimization ◽  
Machine Learning Algorithms ◽  
Application Development ◽  
Machine Learning Applications ◽  
And Control

Machine learning provides the system to automatically learn without human intervention and improve their performance with the help of previous experience. It can access the data and use it for learning by itself. Even though many algorithms are developed to solve machine learning issues, it is difficult to handle all kinds of inputs data in-order to arrive at accurate decisions. The domain knowledge of statistical science, probability, logic, mathematical optimization, reinforcement learning, and control theory plays a major role in developing machine learning based algorithms. The key consideration in selecting a suitable programming language for implementing machine learning algorithm includes performance, concurrence, application development, learning curve. This chapter deals with few of the top programming languages used for developing machine learning applications. They are Python, R, and Java. Top three programming languages preferred by data scientist are (1) Python more than 57%, (2) R more than 31%, and (3) Java used by 17% of the data scientists.

MOBILE APPLICATIONS FOR THE ANDROID OPERATING SYSTEM: DEVELOPMENT TECHNOLOGIES

2021 ◽  
Author(s):  
Виктор Михайлович Красноусов ◽  
Леонид Вячеславович Букреев ◽  
Георигий Андреевивич Шпаковский ◽  
Евгений Романович Калюжный ◽  
Наталья Вячеславовна Зариковская
Keyword(s):  
Operating System ◽  
Programming Languages ◽  
Programming Language ◽  
Mobile Applications ◽  
System Development ◽  
Server Side ◽  
Python Programming Language ◽  
Android Platform ◽  
Android Operating System ◽  
Python Programming

В статье рассмотрены технологии, используемые для реализации мобильных приложений для платформы Android, на языке программирования Kotlin и архитектуры MVVM, а также реализации их серверной части на языке программирования Python. The article discusses technologies for implementing an application for the Android platform in the Kotlin and MVVM programming languages, as well as the implementation of the server side in the Python programming language.

Python programming language: practicum

2019 ◽  
Author(s):  
Роман Жуков ◽  
Roman Zhukov
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Undergraduate Students ◽  
Object Oriented Programming ◽  
Federal State ◽  
Full Time ◽  
Data Types ◽  
Python Programming Language ◽  
State Educational ◽  
Python Programming

The tutorial is devoted to the theoretical and practical study of the modern widely used programming language Python. The manual consists of 5 chapters, which consistently addressed issues such as the history of programming languages, features and basic elements of the Python programming language (data types; instructions, functions, modules; object-oriented programming; development of graphical interfaces). The material is presented compactly while maintaining the necessary rigor, algorithmicity and detailed elaboration of the basic concepts in accordance with the working program of the discipline "Computer workshop". Meets the requirements of the Federal state educational standard of higher education of the last generation. For undergraduate students full-time and part-time training areas "Business Informatics", as well as all those interested in programming.

Is Python an Appropriate Programming Language for Teaching Programming in Secondary Schools?

2015 ◽  
Vol 4 (2) ◽  
pp. 5-14 ◽  
Author(s):  
Eva Mészárosová
Keyword(s):  
Secondary School ◽  
Secondary Schools ◽  
Programming Languages ◽  
Programming Language ◽  
Secondary School Students ◽  
School Students ◽  
Python Language ◽  
Python Programming Language ◽  
Python Programming ◽  
Selection Of

Abstract A variety of programming languages are used to teach fundamentals of programming in secondary schools in Slovakia. Nowadays, we observe a new trend, the Python language gaining ground. In our paper we evaluate the interviews, in which we asked teachers with years of pedagogical experience, what the reasons for selecting a particular programming language where. By analysing the responses we learn about their experience with teaching programming and create a list of the important elements in the selection of the most suitable programming language for secondary school students. We will seek an answer for the question whether the Python programming language is appropriate for all secondary school students.

scholarly journals ENCODING OF CATEGORIAL FEATURES IN NEURAL NETWORKS

2021 ◽  
Vol 2021 (1) ◽  
pp. 3-8
Author(s):  
Denis Barkov ◽  
Svetlana Senotova
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Mathematical Model ◽  
Programming Language ◽  
Data Preparation ◽  
Machine Learn ◽  
Python Programming Language ◽  
Coding Method ◽  
Python Programming

The relevance and areas of application of machine learning are investigated, one of the machine learn-ing algorithms - neural networks, as well as one of the data preparation processes before extracting a mathematical model - the coding of categorical features using the target coding method is consid-ered. Implemented a coding algorithm in the Python programming language

scholarly journals Voice Assistant based Telecommunication System (Tele-Bot)

2020 ◽  
Vol 9 (4) ◽  
pp. 1463-1465
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Programming Language ◽  
Voice Recognition ◽  
Telecommunication System ◽  
Python Programming Language ◽  
Artificial Intelligence Technology ◽  
Scripting Language ◽  
High Level ◽  
Python Programming

In this research we are aiming to plan, develop and deploy a model which is based on voice recognition. We trying to inculcate algorithm which are based on machine learning and also using artificial intelligence technology. We are learning the stages of voice recognition technology, depth of its working accuracy, probabilistic use cases, and system friendliness with the help of Python Programming Language. In order to increase the efficiency of system we are going to take response time into consideration which is crucial requirement into current environment. Python is easy to learn, High Level, Power full programming Scripting language. Fully developed voice recognition modules are to be used for development of our research oriented topic

scholarly journals Machine Learning-Based Technique for Image Classification and Identification of Similarity for Commonness of Source

2020 ◽  
Vol 9 (6) ◽  
pp. 544-548
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Edge Detection ◽  
Image Classification ◽  
Programming Language ◽  
Python Programming Language ◽  
Reserve Bank ◽  
Python Programming ◽  
Highlight Extraction ◽  
Reserve Bank Of India

In India Every year RBI (Reserve bank of India) faces the issue of fake currency. Fake Currency has consistently been an issue that has made a lot of chaos in the market. The expanding mechanical progressions have made the opportunities for making progressively fake currency which is circled in the market which decreases the general economy of the nation. There are machines present at banks and other business regions to check the validness of the monetary forms. Be that as it may, a typical man doesn't approach such frameworks and henceforth a requirement for a product to distinguish counterfeit cash emerges, which can be utilized by average folks. This proposed framework utilizes Image Processing to identify whether the currency is real or fake. The framework is structured utilizing Python programming language and OpenCV. It comprises of the means, for example, grayscale detection, edge detection, Highlight Extraction, and so forth which are performed utilizing reasonable strategies. And which will be further implemented in the Framework for Classification and Identification of Similarity for Commonness of Source

scholarly journals Design and Fabrication of Emergency Drone Recovery System

2020 ◽  
Vol 9 (5) ◽  
pp. 424-427
Keyword(s):  
Programming Language ◽  
Safety Issue ◽  
Raspberry Pi ◽  
Accelerometer Sensor ◽  
The Past ◽  
Python Programming Language ◽  
Recovery System ◽  
Python Programming ◽  
Time Movement ◽  
New System

The drone market has seen a surge in the past few years and the number of consumer drones has been on the increase. With even beginners starting to fly drones, there is a serious safety issue of whether the drone will crash because of technical and unforeseen problems. It may lead to injury of people going about their day and may even cause damage to material things on the ground and naturally damage the drone itself. So, there is a need for a new system which would substantially prevent these kinds of problems. The Emergency Drone System (EDR) will be a solution and will be a versatile fit in all drones. The EDR system uses the MPU-6050 gyroscope and accelerometer sensor along with MPL3115A2 Pressure based Altitude sensor to get input on the real-time movement of the drone and analyses using the algorithm coded into the Raspberry Pi using Python programming language. Apart from this, it also inputs data from the flight controller and analyses it. The parameters such as the altitude, rate of rotation and rate of fall are calculated and based on the algorithm if any kind of anomaly is detected it is programmed to deploy the parachute which will automatically prevent the crashing of the drone. So by which the crashing of drone and damage to property is prevented and safety of people below the drone is ensured.

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