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  "body_markdown": "Data science according to Wikipedia is defined as\n\"Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.\"\nMany people have this notion that Data Science just means training Machine Learning models but it is an amalgamation of various fields. A person must have knowledge of statistics, cloud technologies, coding and databases to become a data scientist. With the increasing change in technology knowledge of DevOps for Machine Learning(known as MLOps) and AutoML is also necessary.\nKaggle the largest community of Data Scientists conducted a survey and based on that survey I am presenting the list of different tools and technologies widely used in different domains of Data Science. Feel free to add some other tools you know which are popular and not mentioned in this list.\nMachine Learning Frameworks\nMachine Learning is one of the core technologies associated with Data Science. Python and R are the widely used languages for ML. The most popular frameworks are based on Python namely scikit-learn, Tensorflow and PyTorch.\nScikit-learn\nTensorflow\nKeras\nXgboost\nPyTorch\nLightGBM\nCaret\nCatboost\nProphet\nFast.ai\nTidymodels\nH2O 3\nMXNet\nJAX\nEnterprise Machine Learning Tools\nMost of the beginners don't know about the tools for ML on cloud, these are some of the best enterprise ML tools by software giants like Google, Amazon and Azure.\nAmazon SageMaker\nGoogle Cloud Vertex AI\nAzure Machine Learning Studio\nGoogle Cloud Vision AI\nGoogle Cloud Natural Language\nAzure Cognitive Services\nAmazon Rekognition\nGoogle Cloud Video Ai\nAmazon Forecast\nBusiness Intelligence Tools\nBusiness Intelligence means analyzing data of companies and giving reports and predicting sales and markets. It is one of the most popular use cases of datascience and deals mainly with Statistics and Data Visualization. Some of the most popular Business Intelligence tools used in the industry are given below.\nTableau\nMicrosoft Power BI\nGoogle Data Studio\nQlik\nAmazon QuickSight\nSalesforce\nLooker\nAlteryx\nSAP Analytics Cloud\nTIBCO Spotfire\nSisense\nEinstein Analytics\nDomo\nDatabases Used\nDatabases form an important part of DataScience because without data there is no datascience. The different databases used by data scientists all over the world is as follow.\nMySQL\nPostgreSQL\nMicrosoft SQL server\nMongoDB\nSQLite\nGoogle Cloud BigQuery\nOracle Database\nAmazon Redshift\nMicrosoft Azure Datalake Storage\nAmazon Athena\nSnowflake\nAmazon DynamoDB\nMicrosoft Access\nIBM DB2\nGoogle Cloud Firestore\nAutomated Machine Learning (AutoML)\nAutoML is one of the most promising technology of modern era which is growing at an alarming rate. Some of the famous AutoML tools are-\nGoogle Cloud AutoML\nH2O Driverless AI\nDataRobot AutoML\nDatabricks AutoML\nCover Image Cartoon vector created by vectorjuice -\nwww.freepik.com",
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