Essentials of Deep Learning and AI

Essentials of Deep Learning and AI curates the essential knowledge of working on deep neural network techniques and advanced machine learning concepts. This book is for those who want to know more about how deep neural networks work and advanced machine learning principles including real-world examples.

This book includes implemented code snippets and step-by-step instructions for how to use them. Youll be amazed at how SciKit-Learn, Keras, and TensorFlow are used in AI applications to speed up the learning process and produce superior results. With the help of detailed examples and code templates, youll be running your scripts in no time. You will practice constructing models and optimise performance while working in an AI environment.

Readers will be able to start writing their programmes with confidence and ease. Experts and newcomers alike will have access to advanced methodologies. For easier reading, concept explanations are presented straightforwardly, with all relevant facts included.

KEY FEATURES

* Extensive examples of Machine Learning and Deep Learning principles.
* Includes graphical demonstrations and visual tutorials for various libraries, configurations, and settings.
* Numerous use cases with the code snippets and examples are presented.

WHAT YOU WILL LEARN

* Learn feature engineering using a variety of autoencoders, CNNs, and LSTMs.
* Get to explore Time Series, Computer Vision and NLP models with insightful examples.
* Dive deeper into Activation and Loss functions with various scenarios.
* Get the experience of Deep Learning and AI across IoT, Telecom, and Health Care.
* Build a strong foundation around AI, ML and Deep Learning principles and key concepts.

WHO THIS BOOK IS FOR

This book targets Machine Learning Engineers, Data Scientists, Data Engineers, Business Intelligence Analysts, and Software Developers who wish to gain a firm grasp on the fundamentals of Deep Learning and Artificial Intelligence. Readers should have a working knowledge of computer programming concepts.

1. Introduction
2. Supervised Machine Learning
3. System Analysis with Machine Learning/Un-Supervised Learning
4. Feature Engineering
5. Classification, Clustering, Association Rules, and Regression
6. Time Series Analysis
7. Data Cleanup, Characteristics and Feature Selection
8. Ensemble Model Development
9. Design with Deep Learning
10. Design with Multi Layered Perceptron (MLP)
11. Long Short Term Memory Networks
12. Autoencoders
13. Applications of Machine Learning and Deep Learning
14. Emerging and Future Technologies.

Shashidhar Soppin has two decades of experience in the IT industry. At present he is working as an Enterprise Architect in Zeta. Earlier, he has worked as DMTS (Distinguished Member of Technical Staff) with progressive history of defining vision, strategy, and technical roadmap, architecting solutions, recommending new approaches via technology enablement and managing large-scale & complex IT projects as part of Wipro. He has worked on, Multi-Cloud (OpenStack, Azure/AWS), Cloud Native Technologies, AIX-OS, HCI (Hyper Converged Infra), Docker Containers and Kubernetes for microservices-based architectures and in Virtualization domains. His areas of interest include AI/ML, Deep Learning and IoT. He has granted and filed patents on various technologies in his name. He is an avid Author for the OSFY Magazine, Written Articles on Micro-services and Kubernetes, Docker, OpenStack, Storage, Node Red, ML & DL to name few {https://opensourceforu.com/author/shashidharsoppin/}. He has also written articles for Medium.com and Research-gate and also a blogger for “Linux-techi”. He has presented papers in conferences and panel speakers in industry forums. He has worked for various organizations including IBM-ISL, Ness Technologies before joining Wipro. He got certified from Great Learning Institute on Deep Learning Technology, Deep Learning Specialization from Coursera and has various Cloud certifications.

Blog Link: https://www.linuxtechi.com/author/shashidhar/

Linkedin Bio: Shashidhar Soppin

Dr. Manjunath Ramachandra has a blend of experience over twenty five years in the verticals of Healthcare, Telecom and consumer electronics spanning the technologies such as signal & Image processing, Artificial intelligence, cloud computing, IoT, wireless communication and quantum computing. He worked for the companies such as Tata Consultancy Services, Royal Philips and was placed in Wipro Limited as principal consultant. He has filed about 90 patents, authored 210 Research papers in international conferences and journals and a book. He was a member of the embedded systems special interest group at NASSCOM. He represented the industry in international standardization bodies such as Wi-Fi Alliance, served as the editor for the regional profiles standard in Digital living network alliance (DLNA) and as the industry liaison officer for the CE-Linux Forum. He has delivered over 24 keynote speeches and conducted over 21 workshop and tutorial sessions. He figures in Marquis Who’s Who 2008 & “2000 outstanding intellectuals of the 21st century”, International Biographical Center, UK. His areas of interest include Deep Learning/ Artificial intelligence, Signal & Image processing and wireless communications.

B N Chandrashekar, a principal consultant by designation is a veteran of Wipro Technologies Limited and has industry experience of around 20 years. He has toned his credibility by owning and getting molded in the roles of Researcher, Consultant, Technical Director and Full Stack AI Consultant. He has work experience in cutting edge technologies and adapts to any new technology in a short time. He has experience in writing proposals, hands-on in multiple high-level programming and scripting languages. He has contributed to programs and tools to open source, co-authored journals and conference papers. He has co-authored publications to online portals like medium.com, research-gate, and OSFY.com. He has pioneered the webinars to university professors at Wipro and colleges on explainable AI framework. He has co-authored multiple patents and has got certified from Great Learning Institute on Deep Learning Technology and Quantum Learning from Coursera.