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  • Day 1 - Keynotes

    21st May 2021

  • 87% of AI/ML projects never make it to production. Have you as an organization grappled with it? Do you want to know - How to boost performance of the data science team for your organization? How to build end to end ML lifecycle to deliver actionable insights consistently? How to keep your AI models relevant and impactful? Then tune in to our Women in Data as they take you through PS Bodhi – The Cloud-agnostic enterprise-ready scalable AI-ML platform that covers end-to-end workflow from development to production.

  • Modern surgical room is a data rich environment with humongous amount of data (sensors and video) being generated every single day from endoscopic and laparoscopic procedures. In last few years, artificial intelligence and specifically deep learning, has pushed the boundaries of state of the art in video analysis tasks such as video object segmentation, video summarization, video action recognition etc. Please join us in this talk on technological overview of video analysis using deep learning and understand specific use cases in surgical domain, significantly advancing clinical care and patient outcomes.

  • To be a successful data scientist, certain skills are essential – all of which are gender neutral. Despite this, there is a gender diversity problem in this field. This vast structural constraint significantly affects the quality of algorithms and subsequent business outcomes which impedes efforts to scale enterprise data science programs to the next level. It is therefore imperative to understand the root causes and develop proactive solutions which mitigate bias both within data science community and in algorithmic systems. As experienced consultants in the Advanced Analytics practice at Kearney, we have experience working with both long-established commercial giants such as large CPG firms as well as new age digital natives, across geographies. We have helped clients bridge the gap between present and desired states through application of cutting-edge data science, analytics, and digital transformation. A striking reality that comes across in all cases is the gender skew in the data science department and industry, and how this hinders maximizing the company’s business output. We strongly believe that solving the gender issue in the data science industry is imperative for business transformation in the new era. There are three major factors contributing to this gender skew – long entrenched societal gender biases, cloudy image of Data Science and archaic recruitment methodologies. We will focus on these issue areas, what they mean in the business world and steps to tackle these head-on. The data science industry will be worth USD 140.9B by 2024, and women need to be a part of this revolution.

  • We often hear of ethics being used for risk mitigation methods in AI design and development. Although necessary to the success of AI, risk mitigation only covers half the potential use of ethics when it comes to practically applying high level ethical values to the concrete context of AI systems. If fully utilised, ethics can become a powerful tool used to enable human-centric innovation that both aligns with current regulations and elevates an AI system into a position of competition in the marketplace.

  • Many say that AI is the last innovation to grace the earth, and I agree. Every single industry is being revolutionized by AI and superior data analytics methods whether that be extremely cheap diagnostic systems or automating business processes that have been manual for several years. This sets the ground for why schooling children from a young age on analytics and AI is crucial. In today's day and age, anyone can have the next best technology in mind, access information provided by millions of others on a topic, whether that be a 15-year-old or a 30-year-old, everyone has the same potential, but not aggressively promoting AI education and development early is taking that chance away from young students. These young students are the ones that will be making up the next generation and educating them on analytics and AI early will prove to be a boon. More importantly, educating women in AI has the power to increase female participation in tech by multitudes, AI having applications in every field from political science to fashion.

  • One of the most important requirements in Indian agriculture, is to measure crop yields across hundreds of millions of farms, accurately, timely and at high resolution. RMSI Cropalytics specializes in the measurement of crop yields using AI/ML combined with remote sensing, advanced agri-modelling and meteorological domain expertise. Our experts have trained our machines to look at satellite imagery, identify the crop and predict the crop yield in each visible farm. This is scalable, across millions of farms in multiple districts of India benefitting the government and agri-inputs companies. Join us for a discussion on how AI can be applied in the agriculture space to reduce agrarian distress.

  • The presentation will focus on the significant impact of Analytics with Robotics process Automation. Ericsson prepared a solution to convert and process data using NLP technologies and automate the extracted output to reach the end business users using Robotics Process Automation technologies. The solution also helps to sense the pulse of the meeting using sentiment analytics. We will also discuss about the implementation, deployment solution and metrics which was saved by the business.

  • Selecting the right technology investments will determine enterprise success in the next couple of years. Businesses can leverage cloud, SaaS solutions, IoT, Data & automation to gain agility, scales, and efficiency.

  • World of sports has evolved by leaps and bounds. It is significantly impacted by the Artificial Intelligence. Both data analytics and artificial intelligence are being used in sports in a substantial amount in audience engagement and viewing experience through graphics, stats, replays, AR/VR, in creating a strategy for games, help coaches through ream time analysis and also in Match predictions, Player predictions and so forth. With lot of synergies it has with the demand of the sports fans, clubs, coaches and players, there is not an iota of doubt that it will immensely flourish this domain.

  • As virtually all industries are adopting Machine Learning at a rapidly accelerating pace, successful deployments and effective operations have emerged as the major bottleneck to getting expedient value from ML systems. Learn why MLOps is emerging as one of the hottest topics.

  • Machine learning and artificial intelligence have long been heralded as the future of transformative technologies. They have been touching every aspect of our life and changing the world around us. When it comes to the med-tech world, the potential for AI and ML technologies is enormous and reaches every corner of it, from diagnostic and imaging technologies to therapeutic applications and robotics.AI can enhance the surgeon’s or practitioner’s capabilities and give him/her “super human” perception, dexterity, and information with which to make better decisions during diagnosis, treatment delivery, surgery and post-operative care.

  • At a high level shall cover what is AI emphasizing on healthcare. Briefly talk about the challenges of leveraging AI in healthcare. Finally discuss how the industry can adapt to AI.

  • Day 2 - Workshops

    22nd May 2021

  • As human civilization steps deeper into the digital era, data & information find their rank going higher in the list of most valued assets by organizations, while processing data into sophisticated solutions takes a front lead in human development as a whole. This led to achieving great results through more scientifically driven decisions across industries and hence rapidly expanded its spectrum to touch upon all possible aspects of the society and human behavior. Now this, with all benevolent intentions, run into the risk of being misused if not protected with appropriate measures of ethics and fairness. Legal and Compliance policies largely safeguard this subject, but framing regulatory measures and implementing governance policies take time for good reason, hence it is imperative for the organizations to adopt ongoing process of self-evaluation and protection. The Key-note aims at reflecting the aspects of AI Ethics and Data Privacy in today’s world and the role of analytics in that.

  • Key aspects to watch out for, while building value add analytics

  • Automation is the key to become more efficient in industrial processes or corporate business metrics. The key to automating a process involves an in-depth understanding of time series data across different verticals. Time-series data analysis helps in finding the issues in the system and also forecast the values to prepare for the future. Time series forecasting is used in many domains like weather forecasting, stock market, energy demand, retail etc. In this workshop, we are going to learn about time series data and its characteristics. We will learn about some of the baseline methods and deep learning techniques to predict time series data.

  • In order to create a more gender-inclusive AI industry, it's important to address the skill gap that exists today and this cannot happen overnight. Bridging the demand-supply gap starts with education that focuses on building necessary lifeskills that make our future workforce job-ready. Moreover, building and nurturing an innovator mindset will transform the way our children think about and choose their career paths. This is specifically so the case with girls and women, who look for a tribe that they can belong to. Creating that conducive environment from them to thrive it at a very young age, in order to create this tribe and to feel belonged, and eventually lead these tribes is critical.

  • Data Science & Data Analytics has become the need of the hour in the education industry. Teacher data literacy is directly related to student outcomes. Teachers today need to collect, analyse and interpret data on a regular basis while teaching in the classroom. This data can also inform a teacher about her/his teaching methods and bring an improvement in her/his performance.

  • This session will take you through Manisha's journey as a technology leader and starting up LogiNext, a global SaaS product that is redefining the way enterprises use technology to manage their supply chain.

  • Education/training, background Key traits needed for success in AI How do you build an AI business? What are the challenges? How has it been being a woman in AI? Why is it important to have more women in AI? Lessons learned

  • In this workshop, we will know about medical images, their types and formats. We will also clear our misconceptions about various types of deep learning problems. We will learn what are binary, multiclass & multilabel classifications and how they differ from each other. We will also see how classification is different from semantic segmentation and instance segmentation with a hands-on example on each type. Further, you will know about Sequential and Functional model architectures, how to build basic model from scratch and use existing tf.keras model api, train model from scratch and use transfer learning.

  • Celebrating Tech Leaders Driving Disruption & Innovation in Data Science & AI