Bayesforge Integrations

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.

Octave lets you securely extract, orchestrate, and act on data from your industrial assets to the cloud. Pull and normalize data from virtually any type of industrial equipment via popular industrial protocols (Modbus, CANopen). Get the right data, at the right time, with the right priority, to the right system. Update your Industrial Internet of Things (IoT) application as your business needs change. Protect your data from the edge to the cloud even as new threats emerge. Octave securely integrates edge devices, networks, and cloud APIs into a single solution, so you can focus on your data. Octave eliminates the need to build IoT infrastructure from scratch, so you can concentrate on creating innovative Industrial IoT applications. Octave frees you from the complexities of Industrial IoT application development with an easy programming interface that uses a common JavaScript framework, supporting the most popular and extensively used industrial protocols such as Modbus, CANopen, etc.

Use our suite of applications to support your quantum research and development needs. Copy your API token, track jobs, and view quantum compute resources. Explore service and API documentation to start working with IBM Quantum resources.

Our singular focus is to help customers achieve real value by using quantum computing for practical business applications. You may be surprised to learn that our enterprise customers have already built hundreds of quantum applications across many industries. The powerful combination of the Advantage™ quantum system and the Leap™ hybrid solver services enable the first in-production quantum applications demonstrating business benefit. D-Wave is the practical quantum computing company delivering real business value for manufacturing, supply chain and logistics, scheduling, and mobility applications today. Quantum computing is already helping to optimize many key parts of the value chain in Industry 4.0.

We make it possible for everyone to think bigger, create faster, and see further. By infusing AI and machine learning, our quantum solutions give you the power to solve the world’s most important and pressing problems. Thermodynamics sparked the Industrial revolution. Electromagnetism ushered in the information age, now, quantum computers are harnessing the unique information processing capability of quantum mechanics to exponentially reduce the time and energy needed for high-impact computing. With the first paradigm-shifting advance since the integrated circuit, quantum computing is poised to transform every global market. The gap between first movers and fast followers will be difficult to overcome.

Cirq is a Python software library for writing, manipulating, and optimizing quantum circuits, and then running them on quantum computers and quantum simulators. Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum computers, where details of the hardware are vital to achieving state-of-the-art results. Cirq comes with built-in simulators, both for wave functions and for density matrices. These can handle noisy quantum channels using monte carlo or full density matrix simulations. In addition, Cirq works with a state-of-the-art wavefunction simulator: qsim. These simulators can be used to mock quantum hardware with the quantum virtual machine. Cirq is used to run experiments on Google's quantum processors. Learn more about the latest experiments and access the code to se how to run them yourself.