Webinar: Building Deep Learning Applications For Big Data By Intel
Deep learning, a subset of artificial intelligence is driving immense advancements in a range of disciplines such as self-driving cars, chatbots and even in healthcare. With Deep Learning becoming one of the most sought after fields for tackling business problems, a key constraint is understanding the broad landscape of tools and frameworks available. Users are looking to execute data-heavy workloads for a range of deep learning applications and train complex models, however challenges arise in  getting the right production environments to deliver value from deep learning investments. In this webinar, Building Deep Learning Applications For Big Data by Mukesh Gangadhar, Staff Lead, APJ Part of the Compute Performance & Developer Products (CPDP) who comes with 18 years of industry experience and has worked extensively on optimising software applications on x86 platforms, especially on the cloud and AI side will give the participants an overview of emerging Deep Learning frameworks for Big Data. The webinar will also cover  Analytics Zoo — a unified analytics + AI platform for distributed Tensorflow, Keras and BigDL on Apache Spark. Analytics Zoo, developed by Intel streamlines end-to-end development and deployment and also provides developers with a set of analytics and AI support for the end-to-end pipeline. Key topics covered in the webinar are: With the landscape for tools and frameworks expanding, it can be hard to get started with Deep Learning solutions for big data applications Intel is uniquely positioned to help developers and data scientists in simplifying AI efforts and get started with deep learning solutions with state-of-the art tool which provides end-to-end solution Analytics Zoo comes with built-in deep learning models, such as text classification, recommendation, and object detection and the platform was also recently open-sourced, allowing the wider community to contribute to it This is part of the process at Intel to simplify AI deployments and get started with deep learning solutions with state-of-the art tools from Intel Who Should Attend Data Scientists and Developers looking to apply deep learning technologies to their big data pipelines Data Engineers who are tasked with architecting scalable and stable data pipelines/infrastructure Product Developers looking for state-of-the solutions for implementing solutions Senior Managers and leaders who want to understand how to apply deep learning to their big data platforms Data science enthusiasts who want to understand the applications of deep learning such as NLP, computer vision and align it with their business objectives About the Speaker Mukesh Gangadhar is the Staff lead, APJ part of the Compute Performance & Developer Products (CPDP). He is a staff architect for optimizing software applications on x86 platforms, especially on the cloud and Artificial Intelligence. He has around 18 years industry experience and holds a degree in Bachelors of Engg in Computer Science & Electronics. When: March 27, 11 am IST Register now, click here
Deep learning, a subset of artificial intelligence is driving immense advancements in a range of disciplines such as self-driving cars, chatbots and even in healthcare. With Deep Learning becoming one of the most sought after fields for tackling business problems, a key constraint is understanding the broad landscape of tools and frameworks available. Users are […]
The webinar Building Deep Learning Applications For Big Data by Intel's Mukesh Gangadhar will give participants an overview of DL frameworks for Big Data
["Intel"]
["data science", "artificial intelligence", "Keras", "AI", "ML", "computer vision", "NLP", "deep learning", "analytics", "TensorFlow", "Intel"]
["AI", "artificial intelligence", "ML", "deep learning", "NLP", "computer vision", "data science", "analytics", "TensorFlow", "Keras"]
Richa Bhatia is a seasoned journalist with six-years experience in reportage and news coverage and has had stints at Times of India and The Indian Express. She is an avid reader, mum to a feisty two-year-old and loves writing about the next-gen technology that is shaping our world.