Python is a high level programming script language which emphasizes code readability allows control of one or more software applications. Basically, Python is used for backend Web Development, Data Analytics, Artificial Intelligence, and Data Science.
Many developers use Python to build productivity tools, games as it is easy to use, powerful, versatile,making it a great choice for beginners and experts. Its dynamically typed nature makes it flexible,includes no hard rules and forgiving error easily so program can compile and run. It truly focuses on learning actual programming concepts and not syntax.
Webtunix is a leading Artificial Intelligence Consulting Company working in the field of Machine Learning and Python application development. It is a platform where different projects related to data mining, Web Scraping, data analysis are performed in Python. Python has special libraries like sciPy for scientific and mathematical calculations and numPy for data framing. As a Machine learning as a service, we offering Image Processing Services and designs algorithm using Python to achieve maximum accuracy.
Web development is the concept that encompasses all the activities involved with websites and web applications. Python can be used to build server-side web applications. Webtunix team develops web applications based on Django and Flask framework.
Data mining is the computing process of discovering patterns in large datasets using various techniques like Machine Learning, Artificial Intelligence, Python, etc. Our team expertise in Web Scraping using python interface, quite familiar with packages like Urllib, Beautiful Soup.
Various packages like SciPy, Pandas, IPython and software carpentry courses used for numerical analysis. Our developer’s team uses these packages for solving Data Mining and Data Analysis problems as well as building prediction system.
Webtunix uses both directed and undirected procedures to examine text at ruler, comprising tokenization, clustering, lemmatization, key phrase and entity extraction, classification, and rules-based tagging.
Deep learning is an area of Machine Learning algorithms having multiple layers for feature extraction and transformation, each successive layer uses output from previous layer as an input. Deep Learning includes learning of deep structured and unstructured representation of data and allows to build a solution optimized from algorithm to solve Machine Learning problems.
Pattern recognition primarily cares about the representation. It faces the challenge to deal with images of different sizes, orientations and illumination conditions, or with time signals of arbitrary length and varying offset. Pattern recognition includes preprocessing procedures to normalize observations, to deal with invariants and to define proper features and distance measures.
Python as a flexible tool allows both teaching of traditional procedural programming and modern OOPs. It can be used to teach a large number of transferable skills and appears to be quicker to learn and in combination with its many libraries this offers the possibility of more rapid development.
Most importantly, its clean syntax offers increased understanding and enjoyment. Detail and complexity is hidden in python, hence making easy to use even by a non-programmer.