Introduction to Deep Learning with Caffe2

Course details

Deep learning is one of the most highly sought-after skills in the technology sector. If you want to take a crack at AI, then this course will help you do so. One of the many reasons for choosing Caffe2 for this course is its processing speed as compared to other platforms. Since the basis of the architecture in Caffe2 is CUDA, it provides flexibility in optimizing the code as per the hardware being used.

Youll learn the foundations of Deep Learning, understand how to build neural networks and develop an understanding of convolutional networks, RNNs, Adam, Dropout, BatchNorm and more. Youll be working on various projects throughout this MOOC with a focus on how to train and manipulate a deep neural network effectively. Youll practice all these ideas in Caffe2 using Python programming languages.

By the end of the course, youll gain an understanding of every element of Caffe2 and be able to use the library in the most efficient way.

About the Author

Akash Deep Singh, is the COO and co-founder at Tessellate Imaging and is passionate about combining Artificial Intelligence and Machine Vision. Prior to Tessellate Imaging, he worked on building solutions ranging from novel systems to detect and classify glioma cancer to a real-time stat generation camera solution for basketball players. He was also part of the team which built Indias first panoramic camera where he acted as the Machine Learning lead. He has a vast experience in building real-time object detection and tracking systems. His past projects include autopilot firmware for Search and Rescue drones, building Disguised and Imposter face recognition software, an all-terrain navigation vehicle and sketch to face image matching for forensics. A national cyber olympiad gold medalist, he loves reading books.

Akash earned his B.E. (Hons) degree in Electronics and Instrumentation engineering from BITS Pilani University, India.

Abhishek Kumar Annamraju, is the CTO and co-founder at Tessellate Imaging. His research areas include computer vision, machine learning, NLP and photogrammetry.

As a part of his undergraduate thesis and then continued employment at Tata Elxsi, India, he built and later lead the machine learning and sensor analytics team. He has research papers on cascade classifiers and shape based object analysis, and a research on traffic sign classifier with accuracies reaching upto 99% as per GTSRB stats is one of the state of art solutions available. He participated in the Google Summer of Code (GSoC), 2016, program, working with Open-Detection, to develop a deep learning oriented vision based classifier and an end-to-end GUI based classifier training module. His past projects include image based monitoring solution to curb illegal sand mining, on-road real-time vehicle detection, 3D facial model generation and classification, deep learning based face recognition, and camera auto-calibration for fisheye images (Tesseract Imaging, India). He was also a part of Mahindra rise challenge, 2014, to develop real-time stationary-cam object detection modules. His research work includes projects involving forensic sketch to image matching and biomedical image processing.

He likes playing frisbee in his free time and loves to travel. Abhishek earned a B.E (Hons) degree in Electrical and Electronics engineering rom BITS Pilani University, India.