Data Science Tools

1. DataRobot : It is a global automated Machine Learning platform. With the capabilities of Data Science, Machine Learning, Statistical Modeling, Artificial Intelligence, Augmented Analytics, Machine Learning Operations (MLOps), Time Series Modeling.

1. DataRobot : It is a global automated Machine Learning platform. With the capabilities of Data Science, Machine Learning, Statistical Modeling, Artificial Intelligence, Augmented Analytics, Machine Learning Operations (MLOps), Time Series Modeling.

2. MLBASE : One of the best Data Science tools and provides distributed and statistical techniques that are key to transforming big data into actionable knowledge. It provides functionality to end-users for a wide variety of standard machine learning tasks such as classification, regression, collaborative filtering, and more general exploratory data analysis techniques.

3. Apache Graph : Apache Graph supports high-level scalability. It is an iterative graph processing system that has been specially developed for this purpose. This was derived from the Pregel model but comes with more number of features and functionalities when compared with the Pregel model. This open-source model helps data scientists to utilize the underlying potential of structured datasets at a large scale.

4. Apache Spark : This is another free tool that offers cluster computing in a blink of the eye, which is at lightning bolt speed. Today, a number of organizations are using Spark for processing large datasets. This data scientist tool is capable of accessing diverse data sources, which include HDFS, HBase, S3, and Cassandra.

5. Cascading : It is specifically for data scientists who are building big data apps on Apache Hadoop. It allows users to solve both complex and simple data problems, using cascading. This is because it offers computation engines, data processing, scheduling capabilities, and systems integration framework.

6. TABLEAU : It is a Data Science visualization software with powerful graphics to make interactive visualizations. It can interface with databases, spreadsheets, OLAP (Online Analytical Processing) cubes. It provides the capability of visualizing the geographical data and for plotting longitudes and latitudes in maps.

7. TENSORFLOW : This is an ML tool, which is widely used for advanced Machine Learning algorithms like Deep Learning. It is an open-source and ever-evolving toolkit which is known for its performance and high computational abilities.

8. SAP HANA : It is an effective tool from SAP with SAP HANA Predictive Analysis Library (PAL).

9. MONGODB : This is another Data Analysis tool that is quite popular since it allows cross-platform document orientation. It has a basic query and aggregation framework, but to do more advanced analytics. It is a perfect choice to iterate ML training experiments.