Machine Learning Vs. Deep Learning – An Example Implementation
April 25, 2018
While Machine Learning (ML) and Deep Learning are part of the AI family, this webinar delves into Deep Learning and its different capabilities.
A Deep Learning model is designed to continually analyze data with a logic structure similar to how a human would draw conclusions. To achieve this, Deep Learning uses a layered structure of algorithms called an artificial neural network (ANN). The design of an ANN is inspired by the biological neural network of the human brain. This makes for machine intelligence that’s far more capable than that of standard Machine Learning models.
Deep learning is applied to fields such as:
- computer vision
- speech recognition
- natural language processing
- audio recognition
- social network filtering
- machine translation
- bioinformatics
- drug design
The results produced using Deep Learning are comparable to – and in sometimes superior to – human experts. Deep Learning is what powers the most human-like artificial intelligence.
With frameworks like Caffe, TensorFlow, Theano, Keras, etc., choosing the right platform and the design to build your Deep Learning architecture is important. But first, knowing how Deep Neural Networks work can potentially unleash the true power behind this melange of science and technology.
On demand recording
Meet our panelists
Vinayak Joglekar, CTO, Synerzip | Prime
Vinayak Joglekar is the Co-Founder and Chief Technology Officer of Synerzip. Vinayak built and scaled Synerzip’s project teams by attracting and retaining top-notch talent in the fiercely competitive market in India. He took the entrepreneurial leap in 1983 after he quit a programmer-analyst position in Alfa-Laval.
He is a certified J2EE programmer and an architect with an active interest in Social, Mobile, Cloud and Big Data technologies. Apart from being the CTO, he mentors bright minds in software development and product delivery. Vinayak can be reached at vinayak@synerzip.com.
Krishna Bhavsar
Krishna has spent more than eleven years conceptualizing and delivering platforms on Natural Language Processing, Machine Learning, Social Media Analytics, Chatbots, Deep Learning frameworks and Text Mining. He is an established open source software contributor and has worked across multiple industries such as Hospitality, Banking, Healthcare, and Human Resources. Krishna has published several papers and is also the author of the book, Natural Language Processing with Python Cookbook. He has a Post Graduate Diploma in Business Analytics and Business Administration from Great Lakes Institute, Chennai.
