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Scripting Languages Software
Scripting languages are programming languages that are used to automate tasks and to create complex applications.
JavaScript Libraries
JavaScript libraries are collections of pre-written JavaScript code that developers can use to simplify and accelerate web development tasks. They provide ready-made functions, utilities, and components for handling common challenges such as DOM manipulation, animations, event handling, data formatting, and AJAX requests. By using libraries, developers reduce the amount of repetitive coding needed and ensure greater cross-browser compatibility. Many JavaScript libraries focus on specific areas, such as UI design, data visualization, or state management, making them versatile tools in both front-end and back-end development. They play a vital role in modern web applications by boosting efficiency, improving code quality, and supporting rapid prototyping.
AI Script Generators
AI script generators are software tools that utilize machine learning algorithms to generate a script or screenplay from user input. These tools have been designed to help writers create cinematic stories more quickly and easily than traditional methods. AI script generators operate by using natural language processing to analyze existing scripts and generate new ones based on the parameters provided by the user. They can be used by amateurs or professionals intending to save time in their film, television show, play, or video writing process, as well as increase story structure accuracy and uniqueness.
View more categories (15) for "notepad python script"
18 Products for "notepad python script" with 2 filters applied:
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1
Teradata VantageCloud
Teradata
...Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
Ray
Anyscale
Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries.Starting Price: Free -
3
Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. -
4
Towhee
Towhee
...Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data.Starting Price: Free -
5
scikit-learn
scikit-learn
...This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.Starting Price: Free -
6
Keepsake
Replicate
Keepsake is an open-source Python library designed to provide version control for machine learning experiments and models. It enables users to automatically track code, hyperparameters, training data, model weights, metrics, and Python dependencies, ensuring that all aspects of the machine learning workflow are recorded and reproducible. Keepsake integrates seamlessly with existing workflows by requiring minimal code additions, allowing users to continue training as usual while Keepsake saves code and weights to Amazon S3 or Google Cloud Storage. ...Starting Price: Free -
7
UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. -
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 MapReduce implementations. ... -
9
Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data... -
10
Oracle Machine Learning
Oracle
...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, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression. ... -
11
Chalk
Chalk
Powerful data engineering workflows, without the infrastructure headaches. Complex streaming, scheduling, and data backfill pipelines, are all defined in simple, composable Python. Make ETL a thing of the past, fetch all of your data in real-time, no matter how complex. Incorporate deep learning and LLMs into decisions alongside structured business data. Make better predictions with fresher data, don’t pay vendors to pre-fetch data you don’t use, and query data just in time for online predictions. Experiment in Jupyter, then deploy to production. ...Starting Price: Free -
12
Metal
Metal
...With your API Key, you can use authenticate by populating the headers. Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.Starting Price: $25 per month -
13
MLflow
MLflow
...The MLflow Tracking component is an API 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. -
14
Xilinx
Xilinx
...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. -
15
...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.
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16
Edge Impulse
Edge Impulse
...Collect sensor, audio, or camera data directly from devices, files, or cloud integrations to build custom datasets. Leverage automatic labeling tools from object detection to audio segmentation. Set up and run reusable scripted operations that transform your input data on large sets of data in parallel by using our cloud infrastructure. Integrate custom data sources, CI/CD tools, and deployment pipelines with open APIs. Accelerate custom ML pipeline development with ready-to-use DSP and ML algorithms. Make hardware decisions based on device performance and flash/RAM every step of the way. ... -
17
Comet
Comet
...Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. ...Starting Price: $179 per user per month -
18
InRule
InRule
InRule Technology® provides explainable, AI-powered intelligence automation. The InRule platform empowers its users to delight customers and improve business outcomes by combining process, decision automation and machine learning – without code. InRule acquired explainable AI leader simMachines. InRule Technology also acquired Barium, provider of a widely deployed digital process automation platform. Making automation accessible is at the heart of everything we do. We put the power of...
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