TOP BEST MACHINE LEARNING FRAMEWORK IN 2021

The year 2021 is ready to use Machine learning that will be useful for industrial workings, economic and social. Machine Learning industry is developing at a quick rate and gives sufficient scope to companies to bring the vital change. Throughout recent years, there have been new searches in machine learning. Many organizations have been able to accomplish the business objectives. For developing machine learning there are some platforms as like below: IBM Watson Machine Learning IBM Watson Machine Learning useful to Developers and Data Scientists for machine-learning deployment. Watson Machine Learning simplifies Businesses. Watson Machine learning features One-Click Deployment Deploy any model at Scale Model Operations Auto AI : AI lifecycle management Integrated UI end to end Dynamic retaining R Studio RStudio is an integrated development environment (IDE) for R, which is a programming language for graphics and computing. It has two formats: RStudio Server runs on a remote server and R Studio Desktop use for desktop application. It has syntax-highlighting editor for supporting direct code execution. RStudio IDE Features Execute R code from the source editor. Code completion, Syntax highlighting and smart indentation. Jump to function definitions. Alteryx Alteryx is a data analytics platform designed for business data analysts. It provides share options, centralized analytics deployment and securely hosted to encourage effective collaboration. Analysts store analytics workflows or apps in a private environment. It also adds version controls. Build data models with drag-and-drop workflows Share and Create data insights via reports and apps Blend, analyze and prepare data via repeatable workflows Visualize data models and blends with Alteryx Designer Connect, access & blend business data from multiple sources Share analytic apps within private teams or publicly Use interactive visualizations to confirm model results Drag and Drop predictive tools based on the R language Output spatial analytics to mappings & visualizations Add security and governance with Alteryx Server Anaconda Enterprise Anaconda Machine learning (ML) is a subset of artificial intelligence in which data scientists use statistical models and algorithms and for outcomes and to perform specific tasks. Machine Learning models may “learn from” data sets to improve their image. Anaconda Enterprise has not fixed pricing information product or service. That is common for software service providers and sellers. To obtain current pricing of it contact to anaconda enterprise. To install and download Anaconda is speediest way to start with machine learning or data science. You have to consider miniconda, when you don’t have the disk space for what comes with anaconda. Features Machine/Deep Learning Services Artificial Neural Networks Computer Vision Natural Language Generation Natural Language Processing Model Development Drag and Drop Language Support Model Training Pre-Built Algorithms Deployment Managed Service Scalability Application IBM SPSS Modeler IBM SPSS Modeler is platform from IBM. It gives intelligence to everyday business problems. It provides wide range of entity analytics, text analytics, automated modeling, social network analytics, decision optimization, data preparation and decision management. It has three editions as like below: IBM SPSS Modeler Professional : It gives automated modeling, advanced algorithm, automated preparation and modeling to uncover hidden patterns in structured data and to build predictive models. IBM SPSS Modeler Premium : It gives social network analysis, text analytics, automated modeling. IBM SPSS Modeler Gold : It can build and deploy models into business process. IBM SPSS Modeler Features Natural Language Processing to sentiments in text and to extract concepts. No need of programming for interaction. Integration to Info sphere, Congos and Netezza. Data Preparation and automated modeling capabilities. You can access all unstructured and structured from disparate source. Datbricks Databricks Unified Analytics offers Apache Spark-based unified analytics platform. It also offers a cloud that combines data engineering and data science functions. Amazon Web Services includes features for performance, operationalization and real-time enablement. A Data Science Workspace enables users to build models and explore data. It permits one-click access to preconfigured Machine Learning environments with popular frameworks. With Data bricks as your Unified Data Analytics Platform, you can quickly clean and prepare data at massive scale with no limitations. The platform permits you to deploy and train ML models for all of your artificial intelligence applications. The top advantages with a Databricks Platform are: Make big data simple Innovate with big data Unifying data engineering and data science Google Cloud AI Platform Google Cloud AI offers many products for variety of uses. It has products list like Google BioQuery, Google Cloud AutoML, and Google Tensor Flow. It also offers machine learning stacks in the space. It is fully managed by interoperable models 1) Data Labeling Service 2) Validation via AI Explanations 3) AutoML 4) MLOps via the Pipeline tool 5) Cloud model deployment with Prediction Data Robot Data Robot gives end-to-end process for building, deploying and maintaining AI. It has products like MLOps, Automated Machine Learning and Automated Time Series. Those are also called as fully integrated tool of Data Robot. The integrated tool can be deployed in multiple ways to match business needs and IT requirements. It also offers an enterprise AI platform. The products are powered by open source algorithms. It is fully-managed by AI services. Azure Machine Learning The Azure Machine Learning service allows data scientists and developers to build, train, and deploy machine learning models. It has products like Azure HD Insight, Azure machine learning studio, Machine learning server, Azure Data Factory, Azure Data bricks and Power BI. It has features like expansive MLops capabilities that integrate with DevOps processes. It protects data with confidential computing and differential privacy. Azure Machine Learning supports open-source frameworks and languages like Kubeflow, MLflow, Python, R, ONNX, Tensor Flow and PyTorch. Azure Machine learning platform is secure, trusted platform and designed for responsible Machine Learning app. Open and Interoperable End-to-end MLOps ML for all skills State-of-the-art Responsible ML