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This paper analyses how Time Series Analysis techniques can be applied to capture movement of an exchange traded index in a stock market. Specifically, Seasonal Auto Regressive Integrated Moving Average (SARIMA) class of models is applied to capture the movement of Nifty 50 index which is one of the most actively exchange traded contracts globally [1]. A total of 729 model parameter combinations were evaluated and the most appropriate selected for making the final forecast based on AIC criteria [8]. NIFTY 50 can be used for a variety of purposes such as benchmarking fund portfolios, launching of index funds, exchange traded funds (ETFs) and structured products. The index tracks the behaviour of a portfolio of blue chip companies, the largest and most liquid Indian securities and can be regarded as a true reflection of the Indian stock market [2].

In the article "The Transhuman Future is here" we explored "virtual" humans powered by an AI digital brain, already rolling out in customer service applications, no to mention Balmain campaigns too. This is happening in parallel with the fast expansion of neurotech and cyborgs, bringing us closer to heightened human performance. But what if you could beat death? As a global and modern society, we now have the opportunity to live post-death via griefbots or avatars, now having generated enough data streams to replicate ourselves. If in our digital afterlife we take the form of a virtual human, do we need to rethink death, the mourning process and the circle of life as we know it? In recent years, the idea that ageing is a disease that can be cured is gaining ground, along with its controversial and ethical implications.

The future isn't an accident, it's something we create and it seems our goal is to hack what it means to be human. What was once science fiction is now reality: the first cyborgs are here. A revolution is unfolding in operating rooms, labs, artist, and designer studios across the world. Scientists and entrepreneurs are on a quest to unlock the secrets of the human brain through implantable technology. The documentary "I am Human" by Elena Gaby follows three people with varying degrees of disabilities who have been implanted with brain-computer interfaces allowing them to achieve what was once impossible.

Machine learning has the potential to support aspects of teaching and learning that are currently time consuming and difficult to manage, such as individual project work, collaboration, tutorials and self-directed learning. In 2018, the global Machine Learning in Education market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025. This report focuses on the global Machine Learning in Education status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Machine Learning in Education development in United States, Europe and China. The key players covered in this study IBM Microsoft Google Amazon Cognizan Pearson Bridge-U DreamBox Learning Fishtree Jellynote Quantum Adaptive Learning Market segment by Type, the product can be split into Cloud-Based On-Premise Market segment by Application, split into Intelligent Tutoring Systems Virtual Facilitators Content Delivery Systems Interactive Websites Others Market segment by Regions/Countries, this report covers United States Europe China Japan Southeast Asia India Central & South America The study objectives of this report are: To analyze global Machine Learning in Education status, future forecast, growth opportunity, key market and key players.

Cognitive systems include applications with capabilities to enhance human decisions. These systems take advantage of cognitive computing capabilities of vast data-processing power, adding of channels for data collection, and environmental setting to deliver practical business insights. In addition, they use analytics to process data collected and deliver useful insights. The banking segment was estimated to account for more than 17% value share towards the end of 2017 and is expected to expand at a high CAGR of 13.5% than other segments of the global cognitive systems spending market from 2017 to 2025. In 2018, the global Cognitive Systems market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025.