Machine Learning and Optimization are important part of Data Science and Artificial Intelligence. As the data is growing in every domain and it is predicted as new oil of economy, Machine Learning and Optimization are way/model to explore the data and get new inference and learning about data. These are very helpful in Health sector, education, Industry and for welfare of Society. Hence, it is important to bring awareness among researchers & academicians and train manpower on Machine Learning and optimization to do innovative research work, projects, and create knowledge base.

The workshop is being organized with an intent to provide recent developments and research practices in the field of Logistics and Supply Chain for the students, researchers and practitioners. It is aimed to provide an understanding about the principles and practices, knowledge required in the increasingly complex global business environment and rising difficulties in competitive positioning of firms. Various experts from IIMs, IITs, NITs and Industry along with our internal resource persons will act as resource persons for this workshop.

M. Tech Data Science and Analytics at the Indian Institute of Information Technology – Allahabad, is a four semesters program designed to develop the skills to analyze, interpret and infer from datasets complemented by a solid foundation of mathematical, statistical and information technology skills

The 3-Day Workshop aims at inculcating the concept of Scientific Research amongst the researchers by focusing of the philosophical aspects of theory building and statistical aspects related to theory validation.

The course has the objective of introducing the participants with fundamental of entrepreneurship development so that they can understand the requirements and challenges in this area. The applied aspect of this workshop will be the practical sessions where they can apply this knowledge in decision making. Following are the key learning objectives of this workshop

The Internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the internet, collecting and sharing data. Predictions are made that the number of such devices would reach to 25 billion by this decade and majority of the services would be available through IoT. Naturally, development and maintenance of such IoT based products and services would require sufficient workforce equipped with knowledge of IoT technologies, more so in countries like India where the IoT boom is yet to pick up. With an aim to develop workforce in IoT, this course introduces to students, researchers and academicians the basic concepts of IoT through a practical view with emphasis on design, requirement, data interfacing and capabilities. The course would cover IoT fundamentals, blended with industrial case studies, design and development of IoT systems, cloud computing, and data analysis. Lab sessions will supplement the lectures.

The Fifth IAPR International Conference on Computer Vision & Image Processing (CVIP2020) will be held at Indian Institute of Information Technology Allahabad, Prayagraj, India, from December 4-6, 2020. CVIP is a premier annual conference focused on Computer Vision and Image Processing. With its high quality, it provides a great platform to students, academia and researchers.

Deep architectures are playing the most important role in the area of machine learning and are considered as the future technology and anticipated a complete paradigm shift in the area of artificial intelligence by the researchers. It is considered to be one of the most active areas of research in signal, image, vision and biometrics and comprises of supervised and unsupervised models of approach for detection/ recognition/ classification/ synthesization of objects. With the advent of extraordinary computation power and huge data sets, it is possible to model the most complex processes using deep architectures. With the advent of Deep learning architectures, almost all areas of signal processing have undergone significant changes in their approach. This is primarily because machine learning is at the forefront of solving many problems in computer signal, image, vision and biometrics which were thought to be either unsolvable or highly computationally intensive in the past. One of the key ideas which have facilitated this is the introduction of deep architectures, which form the basis of present day pattern based recognition problems. The proposed one-week course will be comprising of approximately 25 lectures followed by 15 hours’ worth of lab demonstration and hands-on approach is intended to help the participants familiarise themselves with Signal & Image Processing, Computer Vision, Biometrics and Machine Learning and pertains to how all of the approaches can be applied to research problems in real life. The course also covers essentials of machine learning, deep neural networks as well as the other models how they can be applied to solve practical problems in computer vision so that more people become interested in signal processing. Objectives: 1. Providing a platform to showcase the research work through technical paper and poster presentation. 2. Building awareness towards deep learning architectures. 3. Building the technical capacity in the area of Signal, Image, and Vision Processing via deep architectures. 4. Building communities of research students, educator, R&D, and Industry persons in this emerging area of research and development. 5. Providing hands-on tutorial sessions, where the participants can experiment with concepts and methods.