Results for: python cad - Page 3
View:
Suggested Categories:
CAD Libraries
CAD libraries are collections of pre-made design elements, components, or templates that can be used in CAD software to speed up the design process. These libraries typically include 2D and 3D models, parts, symbols, and standards that can be easily integrated into drawings or designs. CAD libraries help engineers, architects, and designers quickly access commonly used objects, materials, and components, improving efficiency and ensuring consistency across projects. They are used in various industries such as manufacturing, architecture, and construction, where standardization and accuracy are crucial.
Architectural CAD Software
Architectural CAD software enables architects, engineers, and designers to create detailed digital drawings, plans, and models of buildings and structures. It offers tools for drafting, 2D and 3D modeling, rendering, and documentation to support the design and construction process. The software often includes features for collaboration, version control, and integration with building information modeling systems to improve accuracy and workflow efficiency. By automating repetitive tasks and providing precise measurement tools, architectural CAD software helps reduce errors and accelerate project delivery. Ultimately, it empowers professionals to visualize, plan, and communicate architectural concepts effectively.
CAD Viewers
CAD viewers are software tools that enable users to open, view, and interact with CAD (Computer-Aided Design) files without requiring full CAD software for editing or creating designs. These viewers allow users to view 2D and 3D drawings, blueprints, and models in various CAD formats, such as DWG, DXF, or STEP, and often provide features like zooming, rotating, and panning. CAD viewers are commonly used in industries such as engineering, architecture, and manufacturing to review designs, collaborate on projects, and share files with stakeholders. Some CAD viewers also offer markup and annotation tools for commenting on designs.
View more categories (20) for "python cad"
201 Products for "python cad" with 2 filters applied:
Sort By:
-
1
Definitive
Definitive
A one-shot prompt-to-visualization API that seamlessly integrates with enterprise & public data, enabling users to instantly & accurately retrieve visually rich answers to their questions. Enables enterprises to engage in dynamic conversations with their own data, fostering efficient collaboration and informed decision-making. Supports Python code generation and joining of disparate data sets. An autonomous data science agent, providing comprehensive support in data analysis, predictive... -
2
Superlinked
Superlinked
... and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
3
TruLens
TruLens
TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack...Starting Price: Free -
4
Fabi.ai
Fabi.ai
Fabi.ai is an AI-powered, collaborative data analysis platform. It helps data teams turn data into insights thanks to a seamless integration between SQL, Python, AI and no-code. From Fabi.ai, data teams can build and share interactive dashboards and reports, data apps, or lightweight data pipelines, pushing insights to Google Sheets and Slack.Starting Price: $199/month -
5
Instructor
Instructor
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition...Starting Price: Free -
6
PandaAI
PandaAI
.... To get started, users can install the pandasai Python library, set up their API key, load their datasets, and push them to the platform for analysis.Starting Price: €20 per month -
7
ML Console
ML Console
...GL, ML Console achieves training speeds comparable to traditional Python-based methods. Its user-friendly interface simplifies the machine learning process, making it approachable for users with no advanced AI expertise. Additionally, ML Console is free to use, eliminating barriers to entry for those interested in exploring machine learning solutions. Starting Price: Free -
8
MLlib
Apache Software Foundation
Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional Map... -
9
Microsoft 365 Copilot Analyst
Microsoft
Microsoft 365 Copilot Analyst is an advanced AI agent designed to transform raw data into valuable insights. By utilizing powerful data analysis capabilities, including Python coding, Analyst helps users make informed, data-driven decisions. It can process complex datasets, generate reports, and uncover trends, all while seamlessly integrating with Microsoft 365’s suite of tools. Analyst empowers users to automate data analysis, saving time and enabling businesses to make better strategic...Starting Price: $30/month -
10
TF-Agents
Tensorflow
... for building custom environments, policies, and networks, facilitating the creation of complex RL pipelines. TF-Agents supports both Python and TensorFlow environments, allowing for flexibility in development and deployment. It is compatible with TensorFlow 2.x and provides tutorials and guides to help users get started with training agents on standard environments like CartPole. -
11
Codespy
Codespy
Codespy AI Detector is a powerful tool designed to identify AI-generated code within software projects quickly and accurately. It supports popular programming languages such as Java, Python, JavaScript, C++, C#, and PHP. The platform helps developers find AI-written code from models like ChatGPT, Gemini, and Claude, which can introduce bugs or unexpected errors. Codespy integrates seamlessly with common development environments like Visual Studio Code and is available as a ChatGPT plugin. Its...Starting Price: $27.98/month -
12
Anyscale
Anyscale
Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode...Starting Price: $0.00006 per minute -
13
Uwear.ai
Uwear.ai
Generate on-model images of your clothing items from a single flat lay photo. Uwear.ai works with any clothing items from t-shirts to dresses and supports different camera zooms and angles. We provide several demo items that are free to generate photos for, so users can assess the quality of the generation before adding their own items.Starting Price: $7 CAD for 10 photos -
14
Azure Machine Learning
Microsoft
.... Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. -
15
Microsoft Cognitive Toolkit
Microsoft
... and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub. -
16
Hopsworks
Logical Clocks
Hopsworks is an open-source Enterprise platform for the development and operation of Machine Learning (ML) pipelines at scale, based around the industry’s first Feature Store for ML. You can easily progress from data exploration and model development in Python using Jupyter notebooks and conda to running production quality end-to-end ML pipelines, without having to learn how to manage a Kubernetes cluster. Hopsworks can ingest data from the datasources you use. Whether they are in the cloud, on...Starting Price: $1 per month -
17
Google Colab
Google
Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation... -
18
Google Cloud Datalab
Google
... knowledge base. Cloud Datalab enables analysis of your data on BigQuery, AI Platform, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions). Whether you're analyzing megabytes or terabytes, Cloud Datalab has you covered. Query terabytes of data in BigQuery, run local analysis on sampled data, and run training jobs on terabytes of data in AI Platform seamlessly. -
19
Replit
Replit
Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup. Start coding with your favorite language on any platform, OS, and device. Invite your friends, teammates, and colleagues right into your code with Google-docs like editing. Import, run, and collaborate on millions of GitHub repos with 0 manual setup. From Python, to C++, to HTML and CSS, stay in one platform to learn and code in any language you want. The second you create a new repl, it...Starting Price: $7 per month -
20
Weights & Biases
Weights & Biases
.... Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence. -
21
... models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
-
22
MLflow
MLflow
... and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects. -
23
Azure Data Science Virtual Machines
Microsoft
... and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.Starting Price: $0.005 -
24
Deepnote
Deepnote
... - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connectionStarting Price: Free -
25
Oracle Machine Learning
Oracle
Machine learning uncovers hidden patterns and insights in enterprise data, generating new value for the business. Oracle Machine Learning accelerates the creation and deployment of machine learning models for data scientists using reduced data movement, AutoML technology, and simplified deployment. Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Notebooks support SQL, PL/SQL, Python... -
26
Xilinx
Xilinx
... the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications. -
27
Tabnine
Tabnine
... completion and an AI-powered chat and supports numerous use cases such as code generation, explanation of code, creating unit tests, generating documentation, debugging code, refactoring and maintaining code. Tabnine is integrated with all the major IDEs such as VS Code, JetBrains, Visual Studio, Eclipse. It supports over 80 programming languages and frameworks including JavaScript, Python, Java, PHP, Go, and more.Starting Price: $12 per user per month -
28
JupyterLab
Jupyter
... and integrate with existing ones. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include, data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala. -
29
Chainer
Chainer
A powerful, flexible, and intuitive framework for neural networks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes... -
30
Deeplearning4j
Deeplearning4j
DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API...