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Info and references

Python

1. Anaconda Downloads:https://www.anaconda.com/distribution/

Podcast

1. Towards Data Science: https://towardsdatascience.com/podcast/home

Clouds

1. AWS: https://aws.amazon.com/
2. Google Cloud: https://console.cloud.google.com/home/dashboard
3. Azure:https://azure.microsoft.com/
4. IBM:https://www.ibm.com/cloud

Algorithm

1. Geek for Geek: https://www.geeksforgeeks.org/
2. NetworkX : https://networkx.github.io/documentation/stable/index.html

Big Data

1. Hadoop: https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/SingleCluster.html

2. Spark: https://spark.apache.org/docs/2.4.4/

3. Elasticsearch:https://www.elastic.co/

4. Neo4j: https://neo4j.com/

5. DataBricks: https://community.cloud.databricks.com/login.html

Data Science

1. Scikit-Learn:https://scikit-learn.org/stable/
2. TensorFlow:https://www.tensorflow.org/
3. Keras: https://keras.io/

Quantum Computing

1. IBM Q-Experience : https://www.ibm.com/quantum-computing
2. Qiskit: https://qiskit.org/documentation/index.html
3. Rigetti: https://www.rigetti.com/systems
4. Quantum Inspire: https://www.quantum-inspire.com/