Deep learning

ColBERT (Contextualized Late Interaction over BERT) is a retrieval model that is designed to strike a balance between the efficiency of traditional methods like BM25 and the accuracy of deep learning models like BERT, an open source deep learning model used for natural language understanding. ColBERT uses the late interaction and MaxSim scoring method to rank the documents based on their relevance to the query. This scoring method furnishes better retrieval because of fine-grained matching and context awareness.

Get an introduction to natural language processing and learn how it can help us to converse more naturally with computers.

Learn about the basics of PyTorch and it's support for the training, evaluation, and inferencing phases of the machine learning workflow.

Learn Python, the most popular programming language for data science and software development. Gain proficiency in using Python libraries like Pandas and Numpy and in developing code using Jupyter notebooks.

Get hands-on experience and learn important techniques for preparing your data for analysis. Then, learn how to gain a better understanding of your data through exploratory data analysis.

Build your data science skills with R and SQL. Master the ability to transform data into information and insights.

Get hands-on experience and learn important techniques for preparing your data for analysis. Then, learn how to gain a better understanding of your data through exploratory data analysis.

Interact with deep search platform for new knowledge explorations and discoveries

Explore the use of machine learning algorithms in threat detection and management.

Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make distributed deep learning fast and easy to use.