Awesome big data github. More than 150 million people use ...

  • Awesome big data github. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. GitHub is where people build software. . Beginners are using them to boost skills faster than ever! GitHub is where people build software. Your This is even truer in the field of Big Data. For beginners and experts. Probably the best curated list of data science software in Python. The Data Stack Show - A show where they talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data 🚀 500+ curated resources for Data Analysis & Data Science: Python, SQL, Statistics, ML, AI, Visualization, Cheatsheets, Roadmaps, Interview Prep. This is a list of topic-centric public data sources <https://github. Inspired by awesome-php, awesome-python, awesome-ruby, hadoopecosystemtable & big-data. Contribute to DataLearns/Awesome-BigData-1 development by creating an account on GitHub. Awesome-bigdata is a curated list of various tools, frameworks, and resources related to big data. A curated list of awesome plugins, themes, agents, projects, and resources for https://opencode. com/awesomedata/awesome-public-datasets> _ in high quality. Home page for awesome collections is located in the awesome-data Explore some of the best open source big data projects you can contribute to on Github and add value to your portfolio with open source contributions. Contribute to NajiElKotob/Awesome-BigData development by creating an account on GitHub. They are collected and tidied from blogs, answers, and user responses. Contribute new data here! Big Data Resources and References. Contribute to 2233admin/Awesome-APIs development by creating an account on GitHub. - krzjoa/awesome-python-data-science 72,994 MIT 11,157 74 61 Updated 5 days ago apd-core Public Core meta for awesome-public-datasets. This open-source project aims to provide developers, data engineers, and data scientists A curated list of awesome big data frameworks, resources and other awesomeness. A curated list of awesome big data frameworks, resources and other awesomeness. - academic/awesome-datascience A curated list of awesome big data frameworks, ressources and other awesomeness These Big Data Projects in GitHub are so clever, we couldn’t stop exploring them. For example, Apache Spark, used by 80% of Fortune 500 companies, has over 2,000 Explore some of the best open source big data projects you can contribute to on Github and add value to your portfolio with open source Which are the best open-source Big Data projects? This list will help you: awesome-scalability, ClickHouse, spark, data-science-ipython-notebooks, flink, gun, and presto. 📚 A curated list of APIs from round the web. Get started with four standout Big Data Projects in GitHub that beginners can build immediately. Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python A curated list of awesome Big Data technologies, documentations and analytics tools. These 10 GitHub repositories provide a wealth of information and resources to help you become a professional data engineer and keep you updated on current trends. Despite a good number of resources available online (including KDnuggets dataset) for large datasets, many ScyllaDB - NoSQL data store using the seastar framework, compatible with Apache Cassandra. The awesome section presents collections of high quality datasets organized by topic. HBase - The Hadoop database, a distributed, scalable, big data :memo: An awesome Data Science repository to learn and apply for real world problems. A curated list of awesome big data frameworks, resources and other awesomeness. ai - awesome-opencode/awesome-opencode Big Data Resources and References. - budacsika/awesome-bigdata A curated list of awesome big data frameworks, resources and other awesomeness. re41w, zdhbr, jax3, 6e9xcx, vmw7, cg5t, 84q50m, 43ja, bxokn, m4eg,