Join our new short course, Embedding Models: From Architecture to Implementation! Learn from Ofer Mendelevitch, Head of Developer Relations at Vectara. This course goes into the details of the architecture and capabilities of embedding models, which are used in many AI applications to capture the meaning of words and sentences. You will learn about the evolution of embedding … [Read more...] about Embedding Models: From Architecture to Implementation
Software Development
Digital Transformation
Designed for leaders focused on implementing new ideas, staying ahead of the competition and aligning their people, data and technology to drive digital transformation. First, we discuss the pace of change, and its impact, implications and opportunities. Traditional businesses need to rethink their underlying assumptions to create new game plans and capture new opportunities … [Read more...] about Digital Transformation
Mastering Streamlined Syntax: Efficient Kotlin Coding
In this guided project, you'll uncover the secrets to writing efficient and clean Kotlin code by mastering its streamlined syntax features. Perfect for developers with a basic understanding of programming and familiarity with object-oriented principles, this project will guide you in building a functional Student Task Management System using Kotlin. Please note this is an … [Read more...] about Mastering Streamlined Syntax: Efficient Kotlin Coding
Apache Kafka – An Introduction
Apache Kafka is a powerful, open-source stream processing platform that enables businesses to process and analyze data in real-time. This course introduces the core concepts and architecture of Apache Kafka, guiding learners. This course is designed for aspiring data engineers, software developers interested in data processing, and IT professionals looking to diversify into … [Read more...] about Apache Kafka – An Introduction
Designing Larger Python Programs for Data Science
Modern programs are complicated structures, with hundreds to thousands of lines of code, but how do you efficiently move from smaller programs to more robust, complicated programs? How do data scientists simulate the randomness of real world problems in their programs? What techniques and best practices can you leverage to design pieces of software that can efficiently handle … [Read more...] about Designing Larger Python Programs for Data Science
