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AI based E-commerce Personalization Startups – Sushrut Tendulkar

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Jumper.ai is an AI-based platform that enables brands and SME's to instantly auto-reply and engage with customers. Its platform features conversational commerce, live chat, automated replies, bot builder, and abandoned cart recovery. Boxx.ai is a Bengaluru based artificial intelligence startup that helps e-commerce companies increase their conversion rates by displaying the most personalised products for each user. Boxx.ai predicts what each visitor is likely to buy next using its proprietary algorithms. This helps consumer internet companies curate a line of products and extend a highly personalised experience to each of its customers.


President Donald Trump's view on covid-19 tests shows he's an algorithm

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Actually, such statements offer a valuable insight into the way the U.S. president's mind works. Of course, testing doesn't create sick people, it merely discovers them. If there were no sick people to discover, testing would not create bad news. So it's logical to dismiss Trump's absurd reasoning out of hand. I did that for weeks.


Technology Coverage - Data, Artificial Intelligence & Advanced Analytics Summit

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In this crazy year of online events, conferences are trying to lure the audience by offering anything and everything under the hood. Promises are being made that hundreds of topics will be covered. Data Platform Virtual Summit 2020 will cover the length and breadth of Azure Data, Analytics & AI stack. Yeah, your favorite SQL Server comes under Azure Data & your lovable Power BI comes under Analytics:). This year we are adding a new track, Industry Solution, which will feature sessions related to Data/Analytics/AI solution-ing for different industries and verticals like BFSI, Manufacturing, Retail, E-Commerce, Healthcare, Utility, Energy, Hospitality & more.


Comprehensive Guide To Learning Rate Algorithms (With Python Codes)

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Learning rate is an important hyperparameter that controls how much we adjust the weights in the network according to the gradient. The question most commonly asked in the field of Machine learning is "how do we know what is the right value for learning rate?" Unfortunately, there is no one size fits all answer to this question. But, I will put forth some of the methods you can use that can help you estimate what value should be used. This article covers the types of Learning Rate (LR) algorithms, the behaviour of learning rates with SGD and implementation of techniques to find out suitable LR values.


Artificial intelligence could improve CT screening for COVID-19 diagnosis

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Researchers at the University of Notre Dame are developing a new technique using artificial intelligence (AI) that would improve CT screening to more quickly identify patients with the coronavirus. The new technique will reduce the burden on the radiologists tasked with screening each image. Testing challenges have led to an influx of patients hospitalized with COVID-19 requiring CT scans which have revealed visual signs of the disease, including ground glass opacities, a condition that consists of abnormal lesions, presenting as a haziness on images of the lungs. "Most patients with coronavirus show signs of COVID-related pneumonia on a chest CT but with the large number of suspected cases, radiologists are working overtime to screen them all," said Yiyu Shi, associate professor in the Department of Computer Science and Engineering at Notre Dame and the lead researcher on the project. "We have shown that we can use deep learning--a field of AI--to identify those signs, drastically speeding up the screening process and reducing the burden on radiologists."


Training a Deep Reinforcement Learning Agent to Play Snake

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Those of us who have ever used a Nokia mobile phone two decades ago will remember the Snake game that was first introduced on the Nokia 6110. An adaption of an arcade game from 1976, it eventually found itself on 400 million phones. Indeed, there is even a "World Snake Day" for nostalgic fans to remember this bygone era. But can you train a deep reinforcement learning agent to play the game? Data scientist Hennie de Harder decided to find out and chronicled her journey of pitting an agent against a Python version of the game in a blog post on Towards Data Science. One of three basic machine learning paradigms, reinforcement learning is an area of machine learning concerned with software agents that take action based on maximizing predefined rewards.


AI in cancer care: how COVID is speeding up adoption

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Scientists have warned there could be thousands of excess deaths in the UK in the coming years due to delays in cancer diagnosis and treatment during by the coronavirus crisis. The pandemic has meant routine screenings, and urgent referrals and treatments, have been delayed or cancelled, leading to a backlog of patients. Researchers at the Health Data Research Hub for Cancer examined data from eight hospital trusts and found that, in a worst-case scenario, if delays continue, there could be up to 35,000 additional cancer deaths within a year. But artificial intelligence (AI) could be a solution. Over the past decade, AI has emerged as a leading technology with the potential to aid the medical community, from speeding up diagnostics and improving accuracy to improving patient outcomes and hospital efficiencies.


Automating the fight against large-scale cyberthreats during and post-pandemic - Intelligent CIO Europe

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Artificial Intelligence and Machine Learning are important components in helping enterprises maintain organisational resilience and detect cyberthreats. Asher De Metz, Lead Senior Consultant at Sungard AS, discusses the benefits of using this technology to become more cyber-aware. The COVID-19 pandemic continues to be an immense humanitarian crisis that is severely impacting the global economy. As organisations have shifted to remote working to protect employees while continuing to serve customers, they have moved the majority of activities to the digital world – increasing the risk of cyberattacks and threatening Business Continuity. According to the World Economic Forum's COVID-19 risks outlook, employers are most worried about COVID-19 provoking a prolonged recession, followed by a surge in bankruptcies.


Top 10 Books for Machine Learning You Should Read

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Now for all those of you who are really good at coding but have a bad background in mathematics, this is the book for you guys to go with. Do not think of hackers as someone related to Cyber-Security but hacker here refers to those who are already good at coding. This book stresses deeply on the math that is required for Machine Learning and uses real-world scenarios and use-cases which can help you get a hang of it. Typical Machine Learning problems with R programming language are the start and move to advanced topics where you will be taught how to build a recommendation system and those sorts of applications. It is the book to study if you are already comfortable with advanced coding.


Exploring the NoSQL Family

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Knowledge on NoSQL databases seems to be an increasing requirement in data science applications, yet, the taxonomy is so diverse and problem-centered that it can be a challenge to grasp them. This post attempts to shed light on some of the concepts, often delving into each design's specificities. We start by briefly introducing NoSQL and the reasoning behind its appearance, followed by an analysis of each of the four members of the NoSQL family, their behavior, and main mechanisms, in addition to their advantages, disadvantages, and typical use cases. NoSQL (Not-only SQL) came into prominence in the mid-late-2000s as alternatives to traditional SQL. Instigated by the Web 2.0 industry, it allows for horizontal scaling, distributed databases, and flexible models (schema-less design).