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Summary |
Deepnote is a collaborative virtual notebook which allows data scientists to instantly collaborate and quickly deploy data within a team. It is a browser-based service which can be used across any platform, such as Windows, Mac, Chromebook or Linux, without requiring any additional downloads. Users can create projects in the notebook consisting of the code and the data, and running in one environment. It can be shared with other people who can use it simultaneously. This collaboration feature allows data scientists to review other notebooks, present their work to colleagues instantly, and transfer their models to the engineering teams. The platform increases the user’s productivity during tasks like exploring and cleansing data or building ML models. The main features that ensure this include variables and better plots, code intelligence, and shortcuts and command palette. The notebook integrates easily with the existing infrastructure and workflows and with other platforms like GitHub and GitLab, MongoDB, and S3 buckets. Deepnote makes working with datasets easy and secure. ..show more |
Databricks is a compact data management platform that enables businesses to unify their analytics, data and AI, storing them all in a secured location. Users get to unify their entire data ecosystem belonging to different standards and formats. The software includes collaborative features allowing team members to work together across the entire data and AI workflow. It also brings collaborative notebooks within a unified portal enabling companies to work easily with Python, R SQL and Scala. Databricks includes openness and flexibility which provides reliability and performance within the data warehouses. These qualities of the platform make it a perfect solution for structured, unstructured and semi-structured data types. With Databricks, businesses can use their existing BI tools to analyse the updated metrics in real-time. Furthermore, the software also comes equipped with a heap of solutions facilitating a complete ML lifecycle management which supports any data type across multiple scales. This ML lifecycle also enables businesses to train models and manage their deployment in a way that best serves their individual purposes. ..show more |
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Candidate Code
Databricks
Hex
CoLab
GPT Mind Maps Maker
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Top alternatives to Databricks
AWS Cloud9
Synapse Medicine
Spark CMS
Snowflake
IFTTT
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