Do you worry you could lose your job to a robot?

4 stars based on 36 reviews

Tools of static analysis, linters and looking for auto trading robot api workers or working quality checkers. Libraries for visualizing data. Frameworks for Neural Networks and Deep Learning. Libraries for Machine Learning. Libraries for accessing third party services APIs. Your looking for auto trading robot api workers or working are always welcome!

Please take a look at the contribution guidelines first. I will keep some pull requests open if I'm not sure whether those libraries are awesome, you could vote for them by adding: Pull requests will be merged when their votes reach If you have any question about this opinionated list, do not hesitate to contact me vinta on Twitter or open an issue on GitHub.

Awesome Python A curated list of awesome Python frameworks, libraries, software and resources. Ajenti - The admin panel your servers deserve. Grappelli - A jazzy skin for the Django Admin-Interface. Algorithms and Design Patterns Python implementation of algorithms and design patterns. PyPattyrn - A simple yet looking for auto trading robot api workers or working library for implementing common design patterns.

Asset Management Tools for managing, compressing and minifying website assets. Audio Libraries for manipulating audio. Feature Extraction, Classification, Segmentation and Applications pydub - Manipulate audio with a simple and easy high level interface. TimeSide - Open web audio processing framework. Authentication Libraries for implementing authentications schemes.

Flask-OAuthlib - OAuth 1. Build Tools Compile software from source code. BitBake - Looking for auto trading robot api workers or working make-like build tool for embedded Linux. PlatformIO - A console tool to build code with different development platforms.

PyBuilder - A continuous build tool written in pure Python. SCons - A software construction tool. Built-in Classes Enhancement Libraries for enhancing Python built-in classes. Box - Python dictionaries with advanced dot notation access. Kotti - A high-level, Pythonic web application framework built on Pyramid.

Mezzanine - A powerful, consistent, and flexible content management platform. Wagtail - A Django content management system. Caching Libraries for caching data. Beaker - A library for caching and sessions for use with web applications and stand-alone Python scripts and applications. DiskCache - SQLite and file backed cache backend with faster lookups than memcached and redis. HermesCache - Python caching library with tag-based invalidation and dogpile effect prevention.

ChatOps Tools Libraries for chatbot development. Errbot - The easiest and most popular chatbot to implement ChatOps. Code Analysis Tools of static analysis, linters and code quality checkers. Code Analysis flake8 - A wrapper around pycodestyle, pyflakes and McCabe.

Static Type Checkers mypy - Check variable types during compile time. Static Type Annotations Generators MonkeyType - A system for Python that generates static type annotations by collecting runtime types Command-line Tools Libraries for building command-line application. Gooey - Turn command line programs into a full GUI application with one line Python-Fire - A library for creating command line interfaces from absolutely any Python object.

PathPicker - Select files out of bash output. Compatibility Libraries for migrating from Python 2 to 3. Python-Future - The missing compatibility layer between Python 2 and Python 3.

Python-Modernize - Modernizes Python code for eventual Python 3 migration. Six - Python 2 and 3 compatibility utilities. Computer Vision Libraries for computer vision. SimpleCV - An open source framework for building computer vision applications. Concurrency and Parallelism Libraries for concurrent and parallel execution. Tomorrow - Magic decorator syntax for asynchronous code. Configuration Libraries for storing and parsing configuration options.

ConfigObj - INI file parser with validation. Cryptography cryptography - A package designed to expose cryptographic primitives and recipes to Python developers. Paramiko - A Python 2. Data Analysis Libraries for data analyzing. Looking for auto trading robot api workers or working - Data mining, data visualization, analysis and machine learning through visual programming or scripts.

Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools. Optimus - Cleansing, pre-processing, feature engineering, exploratory data analysis and easy Machine Learning with a PySpark backend. Data Validation Libraries for validating data. Used for forms in many cases. Cerberus - A lightweight and extensible data validation library.

Schematics - Data Structure Validation. Data Visualization Libraries for visualizing data. Altair - Declarative statistical visualization library for Python. Bokeh - Interactive Web Plotting for Python. Matplotlib - A Python 2D plotting library. PyGraphviz - Python interface to Graphviz. Seaborn - Statistical data visualization using Matplotlib. Database Databases implemented in Python. TinyDB - A tiny, document-oriented database. A key-value and object graph database. Database Drivers Libraries for connecting and operating databases.

Date and Time Libraries for working with dates and times. Chronyk - A Python 3 library for parsing human-written times and dates. Pendulum - Python datetimes made easy. Brings the tz database into Python. Debugging Tools Libraries for debugging code.

Pyflame - Attach this Ptracing Profiler to any processes running Python. Perfect for profiling production webservers. Others django-debug-toolbar - Display various debug information for Django. Caffe - A fast open framework for deep learning. Keras - A high-level neural networks library and capable of running on top of either TensorFlow or Theano.

MXNet - A deep learning framework designed for both efficiency and flexibility. Neupy - Running and testing different Artificial Neural Networks algorithms. AI - Game agent framework. Use any video game as a deep learning sandbox. Theano - A library for fast numerical computation.

Ansible - A radically simple IT automation platform. Cloud-Init - A multi-distribution package that handles early initialization of a cloud instance. Docker Compose - Fast, isolated development environments using Docker. Fabric - A simple, Pythonic tool for remote execution and deployment. Fabtools - Tools for writing awesome Fabric files. OpenStack - Open source software for building private and public clouds.

SaltStack - Infrastructure automation and management system. Distribution Libraries to create packaged executables for release distribution. Nuitka - Compile scripts, modules, packages to an executable or extension module.

PyInstaller - Converts Python programs into stand-alone executables cross-platform. Documentation Libraries for generating project documentation.

Bitcoin crypto currency exchange corporation

  • Cara buat bot status fb warna biru di hp

    Geminilaser megaman 6 robot

  • Bitcoin exchange hacked

    Robot unicorn attack 2 cheats download

Cassio bot script status

  • Bitcoin wallet address size

    Usb bitcoin miner uk

  • Cgminer litecoin machines

    8 bit ripple carry adder vhdl code for program

  • Free bitcoin generator ubuntu no survey

    Nem so de bitcoin vive o traderestrategias btc litecoin dash ripple iota ethereum verge 020117

Gamesbotsvcexe games bot application 32 bit

44 comments State electrum wallets

Emercoin bitcointalk slrr

Artificial intelligence , defined as intelligence exhibited by machines, has many applications in today's society. More specifically, it is Weak AI , the form of A. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more. For example, the University of Southern California launched the Center for Artificial Intelligence in Society, with the goal of using AI to address socially relevant problems such as homelessness.

At Stanford, researchers are using AI to analyze satellite images to identify which areas have the highest poverty levels. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries. The use of artificial intelligence in simulators is proving to be very useful for the AOD. Airplane simulators are using artificial intelligence in order to process the data taken from simulated flights.

Other than simulated flying, there is also simulated aircraft warfare. The computers are able to come up with the best success scenarios in these situations. The computers can also create strategies based on the placement, size, speed and strength of the forces and counter forces.

Pilots may be given assistance in the air during combat by computers. The artificial intelligent programs can sort the information and provide the pilot with the best possible maneuvers, not to mention getting rid of certain maneuvers that would be impossible for a human being to perform.

Multiple aircraft are needed to get good approximations for some calculations so computer simulated pilots are used to gather data. It is a rule based expert system put together by collecting information from TF documents and the expert advice from mechanics that work on the TF The performance system was also used to replace specialized workers. The system allowed the regular workers to communicate with the system and avoid mistakes, miscalculations, or having to speak to one of the specialized workers.

The AOD also uses artificial intelligence in speech recognition software. The air traffic controllers are giving directions to the artificial pilots and the AOD wants to the pilots to respond to the ATC's with simple responses.

The programs that incorporate the speech software must be trained, which means they use neural networks. The program used, the Verbex , is still a very early program that has plenty of room for improvement. The improvements are imperative because ATCs use very specific dialog and the software needs to be able to communicate correctly and promptly every time. The Artificial Intelligence supported Design of Aircraft, [4] or AIDA, is used to help designers in the process of creating conceptual designs of aircraft.

This program allows the designers to focus more on the design itself and less on the design process. The software also allows the user to focus less on the software tools.

The AIDA uses rule based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective. In , NASA 's Dryden Flight Research Center , and many other companies, created software that could enable a damaged aircraft to continue flight until a safe landing zone can be reached. The neural network used in the software proved to be effective and marked a triumph for artificial intelligence.

The Integrated Vehicle Health Management system, also used by NASA, on board an aircraft must process and interpret data taken from the various sensors on the aircraft.

The system needs to be able to determine the structural integrity of the aircraft. The system also needs to implement protocols in case of any damage taken the vehicle.

Haitham Baomar and Peter Bentley are leading a team from the University College of London to develop an artificial intelligence based Intelligent Autopilot System IAS designed to teach an autopilot system to behave like a highly experienced pilot who is faced with an emergency situation such as severe weather, turbulence, or system failure.

The Intelligent Autopilot System combines the principles of Apprenticeship Learning and Behavioral Cloning whereby the autopilot observes the low-level actions required to maneuver the airplane and the high-level strategy used to apply those actions.

AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. AI can be used to potentially determine the developer of anonymous binaries. AI can be used to create other AI. There are a number of companies that create robots to teach subjects to children ranging from biology to computer science, though such tools have not become widespread yet.

There have also been a rise of intelligent tutoring systems , or ITS, in higher education. Data sets collected from these large scale online learning systems have also enabled learning analytics, which will be used to improve the quality of learning at scale.

Examples of how learning analytics can be used to improve the quality of learning include predicting which students are at risk of failure and analyzing student engagement. Algorithmic trading involves the use of complex AI systems to make trading decisions at speeds several orders of magnitudes greater than any human is capable of, often making millions of trades in a day without any human intervention.

Automated trading systems are typically used by large institutional investors. Several large financial institutions have invested in AI engines to assist with their investment practices.

Its wide range of functionalities includes the use of natural language processing to read text such as news, broker reports, and social media feeds.

It then gauges the sentiment on the companies mentioned and assigns a score. Its machine learning systems mine through hoards of data on the web and assess correlations between world events and their impact on asset prices. Several products are emerging that utilize AI to assist people with their personal finances. For example, Digit is an app powered by artificial intelligence that automatically helps consumers optimize their spending and savings based on their own personal habits and goals.

The app can analyze factors such as monthly income, current balance, and spending habits, then make its own decisions and transfer money to the savings account. AI, an upcoming startup in San Francisco, builds agents that analyze data that a consumer would leave behind, from Smartphone check-ins to tweets, to inform the consumer about their spending behavior.

Robo-advisors are becoming more widely used in the investment management industry. Robo-advisors provide financial advice and portfolio management with minimal human intervention. This class of financial advisers work based on algorithms built to automatically develop a financial portfolio according to the investment goals and risk tolerance of the clients. It can adjust to real-time changes in the market and accordingly calibrate the portfolio.

Their technology will be licensed to banks for them to leverage for their underwriting processes as well. This platform utilizes machine learning to analyze tens of thousands traditional and nontraditional variables from purchase transactions to how a customer fills out a form used in the credit industry to score borrowers. The platform is particularly useful to assign credit scores to those with limited credit histories, such as millennials.

Robots have become common in many industries and are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. In the automotive industry , a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world: Artificial neural networks are used as clinical decision support systems for medical diagnosis , such as in Concept Processing technology in EMR software.

Other tasks in medicine that can potentially be performed by artificial intelligence and are beginning to be developed include:. Currently, there are over 90 AI startups in the health industry working in these fields. Another application of AI is in the human resources and recruiting space.

There are three ways AI is being used by human resources and recruiting professionals. AI is used to screen resumes and rank candidates according to their level of qualification. Ai is also used to predict candidate success in given roles through job matching platforms.

And now, AI is rolling out recruiting chat bots that can automate repetitive communication tasks. Typically, resume screening involves a recruiter or other HR professional scanning through a database of resumes. Now startups like Pomato, are creating machine learning algorithms to automate resume screening processes. From to , consumer goods company Unilever used artificial intelligence to screen all entry level employees.

Unilever partnered with Pymetrics and HireVue to enable its novel AI based screening and increased their applicants from 15, to 30, in a single year. From resume screening to neuroscience, speech recognition, and facial analysis Yet another development in AI is in recruiting chatbots. TextRecruit , a Bay Area startup, released Ari automated recruiting interface.

Ari is a recruiting chatbot that is designed to hold two-way text message conversations with candidates. Ari automates posting jobs, advertising openings, screening candidates, scheduling interviews, and nurturing candidate relationships with updates as they progress along the hiring funnel.

Some AI applications are geared towards the analysis of audiovisual media content such as movies, TV programs, advertisement videos or user-generated content. The solutions often involve computer vision , which is a major application area of AI. Typical use case scenarios include the analysis of images using object recognition or face recognition techniques, or the analysis of video for recognizing relevant scenes, objects or faces.

The motivation for using AI-based media analysis can be — among other things — the facilitation of media search, the creation of a set of descriptive keywords for a media item, media content policy monitoring such as verifying the suitability of content for a particular TV viewing time , speech to text for archival or other purposes, and the detection of logos, products or celebrity faces for the placement of relevant advertisements. Media analysis AI companies often provide their services over a REST API that enables machine-based automatic access to the technology and allows machine-reading of the results.

While the evolution of music has always been affected by technology, artificial intelligence has enabled, through scientific advances, to emulate, at some extent, human-like composition.

The AI Iamus created the first complete classical album fully composed by a computer. Moreover, initiatives such as Google Magenta , conducted by the Google Brain team, want to find out if an artificial intelligence can be capable of creating compelling art. By analyzing unique combinations of styles and optimizing techniques, it can compose in any style. The company Narrative Science makes computer generated news and reports commercially available, including summarizing team sporting events based on statistical data from the game in English.

It also creates financial reports and real estate analyses. Echobox is a software company that helps publishers increase traffic by 'intelligently' posting articles on social media platforms such as Facebook and Twitter. It then chooses the best stories to post and the best times to post them. It uses both historical and real-time data to understand to what has worked well in the past as well as what is currently trending on the web.

Another company, called Yseop , uses artificial intelligence to turn structured data into intelligent comments and recommendations in natural language.

There is also the possibility that AI will write work in the future. In , a Japanese AI co-wrote a short story and almost won a literary prize. Artificial intelligence is implemented in automated online assistants that can be seen as avatars on web pages.

Currently, major companies are investing in AI to handle difficult customer in the future.