4,003 skills found · Page 14 of 134
tpetricek / Talks:mortar_board: Slides from my recent talks on data science, data journalism, F#, programming language research and philosophy.
bbfrederick / Rapidtiderapidtide - a suite of programs for doing time lag correlation analysis on fMRI data
TheWover / EasyNetSimple packer for arbitrary data using only .NET API calls. Produces a unique signature with every usage. Standalone program and library. Algorithm: Data <-> GZip <-> AES-256 <-> Base64.
shik3519 / Programming Concepts For Data ScienceBasics of programming: algorithms, data structures, object oriented programming
keshavsingh3197 / Pythonthis resporatory have ml,ai,nlp,data science etc.python language related material from many websites eg. datacamp,geeksforgeeks,linkedin,youtube,udemy etc. also it include programming challange/competion solutions
MaLuns / Wallhaven ElectronA wallpaper program based on electron, the data comes from wallhaven.cc's wallpaper client.
abhishek305 / PyBot A ChatBot For Answering Python Queries Using NLPPybot can change the way learners try to learn python programming language in a more interactive way. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. We are implementing NLP for improving the efficiency of the chatbot. We will include voice feature for more interactivity to the user. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.The main issue with text data is that it is all in text format (strings). However, the Machine learning algorithms need some sort of numerical feature vector in order to perform the task. So before we start with any NLP project we need to pre-process it to make it ideal for working. Converting the entire text into uppercase or lowercase, so that the algorithm does not treat the same words in different cases as different Tokenization is just the term used to describe the process of converting the normal text strings into a list of tokens i.e words that we actually want. Sentence tokenizer can be used to find the list of sentences and Word tokenizer can be used to find the list of words in strings.Removing Noise i.e everything that isn’t in a standard number or letter.Removing Stop words. Sometimes, some extremely common words which would appear to be of little value in helping select documents matching a user need are excluded from the vocabulary entirely. These words are called stop words.Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form — generally a written word form. Example if we were to stem the following words: “Stems”, “Stemming”, “Stemmed”, “and Stemtization”, the result would be a single word “stem”. A slight variant of stemming is lemmatization. The major difference between these is, that, stemming can often create non-existent words, whereas lemmas are actual words. So, your root stem, meaning the word you end up with, is not something you can just look up in a dictionary, but you can look up a lemma. Examples of Lemmatization are that “run” is a base form for words like “running” or “ran” or that the word “better” and “good” are in the same lemma so they are considered the same.
poojasabnani / DSA For Interviews GirlScript EOPData Structures and Algorithms Course for GirlScript Education Outreach Program Batch 1
dsilvestro / PyRatePyRate is a program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework.
Avicted / Galaxy Visualization RaylibThis project visualizes 100,000 real galaxies in blue and 100,000 randomly distributed galaxies in red. The data is sourced from the GPU programming course at: Åbo Akademi University. Additional redshift survey data is also provided.
viictorjs / RefrapyA Python 3 based program for seismic refraction data processing.
AccelerationNet / Access2csvSimple program to extract data from Access databases into CSV files.
yonycherkos / Applied Data Science With Python SpecializationThe 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
google-research / PlurPLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the datasets. This is done by offering a unified API and data structures for all datasets.
sanusanth / Python Basic ProgramsWhat is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Good to know The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular. In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files. Python Syntax compared to other programming languages Python was designed for readability, and has some similarities to the English language with influence from mathematics. Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses. Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose. Applications for Python Python is used in many application domains. Here's a sampling. The Python Package Index lists thousands of third party modules for Python. Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS. Python's standard library supports many Internet protocols: HTML and XML JSON E-mail processing. Support for FTP, IMAP, and other Internet protocols. Easy-to-use socket interface. And the Package Index has yet more libraries: Requests, a powerful HTTP client library. Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML. Feedparser for parsing RSS/Atom feeds. Paramiko, implementing the SSH2 protocol. Twisted Python, a framework for asynchronous network programming. Scientific and Numeric Python is widely used in scientific and numeric computing: SciPy is a collection of packages for mathematics, science, and engineering. Pandas is a data analysis and modeling library. IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing. The Software Carpentry Course teaches basic skills for scientific computing, running bootcamps and providing open-access teaching materials. Education Python is a superb language for teaching programming, both at the introductory level and in more advanced courses. Books such as How to Think Like a Computer Scientist, Python Programming: An Introduction to Computer Science, and Practical Programming. The Education Special Interest Group is a good place to discuss teaching issues. Desktop GUIs The Tk GUI library is included with most binary distributions of Python. Some toolkits that are usable on several platforms are available separately: wxWidgets Kivy, for writing multitouch applications. Qt via pyqt or pyside Platform-specific toolkits are also available: GTK+ Microsoft Foundation Classes through the win32 extensions Software Development Python is often used as a support language for software developers, for build control and management, testing, and in many other ways. SCons for build control. Buildbot and Apache Gump for automated continuous compilation and testing. Roundup or Trac for bug tracking and project management. Business Applications Python is also used to build ERP and e-commerce systems: Odoo is an all-in-one management software that offers a range of business applications that form a complete suite of enterprise management applications. Try ton is a three-tier high-level general purpose application platform.
BritneyMuller / Colab NotebooksA place for non-technical individuals to access data science & machine learning programs.
Sigfried / SupergroupSupergroup brings extreme convenience and understandability to the manipulation of Javascript data collections, especially in the context of D3.js visualization programming.
suman-shah / Python Example Python is commonly used for developing websites and software, task automation, data analysis, and data visualization. Since it's relatively easy to learn, Python has been adopted by many non-programmers such as accountants and scientists, for a variety of everyday tasks, like organizing finances. write a python program and create a file
djlampert / PyHSPFPython extensions to the Hydrological Simulation Program in Fortran (HSPF), including classes for gathering input data, building input files, performing simulations, postprocessing results, calibrating hydrology process parameters, and forecasting climate and land use change effects on water resources
eth-sri / ZkayA programming language and compiler which enable automatic compilation of intuitive data privacy specifications to NIZK-enabled private smart contracts.
