Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works. | It retains all the features you love from data lakes, with one key twist. Deep Lake is explicitly built for deep learning workflows with image, audio, and video datasets. This saves time on building complex data infrastructure, & enables shipping AI models into production much faster. |
Thousands of models, ready to use;
Automatic API;
Automatic scale;
Pay by the second | Storage agnostic API;
Compressed storage;
Lazy Numpy-like indexing;
Dataset version control;
Integrations with deep learning frameworks;
Distributed transformations;
100+ most-popular image, video, and audio datasets available in seconds;
Instant visualization support in Activeloop platform |
Statistics | |
GitHub Stars - | GitHub Stars 8.9K |
GitHub Forks - | GitHub Forks 691 |
Stacks 53 | Stacks 1 |
Followers 12 | Followers 0 |
Votes 0 | Votes 0 |
Integrations | |

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.

Distributed SQL Query Engine for Big Data

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.