Original Source Here Written by I am a programmer from India, and I am here to guide you with Machine Learning for free. I hope you will learn a lot in your journey towards ML and AI with me. AI/ML Trending AI/ML Article Identified & Digested via Granola by Ramsey Elbasheer; a Machine-Driven RSS Bot via WordPress https://ramseyelbasheer.wordpress.com/2020/12/01/160-data-science-and-machine-learning-projects-solved-and-explained-repost-by-ramsey-elbasheer/

https://news.mit.edu/sites/default/files/styles/news_article__cover_image__original/public/images/202011/MIT-BERT-Lottery-01-Press.jpg?itok=k_b70xTx Original Source Here You don’t need a sledgehammer to crack a nut. Jonathan Frankle is researching artificial intelligence — not noshing pistachios — but the same philosophy applies to his “ lottery ticket hypothesis .” It posits that, hidden within massive neural networks, leaner subnetworks can complete the same task more efficiently. The trick is finding those “lucky” subnetworks, dubbed winning lottery tickets. In a new paper, Frankle and colleagues discovered such subnetworks lurking within BERT, a state-of-the-art neural network approach to natural language processing (NLP). As a branch of artificial intelligence, NLP aims to decipher and analyze human language, with applications like predictive text generation or online chatbots. In computational terms, BERT is bulky, typically demanding supercomputing power unavailable to most

Original Source Here Amazon SageMaker Studio notebooks and Amazon SageMaker notebook instances are internet-enabled by default. However, many regulated industries, such as financial industries, healthcare, telecommunications, and others, require that network traffic traverses their own Amazon Virtual Private Cloud (Amazon VPC) to restrict and control which traffic can go through public internet. Although you can disable direct internet access to Sagemaker Studio notebooks and notebook instances, you need to ensure that your data scientists can still gain access to popular packages. Therefore, you may choose to build your own isolated dev environments that contain your choice of packages and kernels. In this post, we learn how to set up such an environment for Amazon SageMaker notebook instances and SageMaker Studio. We also describe how to integrate this environment with AWS CodeArtifact , which is a fully managed artifact repository that makes it easy for organizations of any s

Original Source Here Ever since Amazon SageMaker was introduced at AWS re:Invent 2017, customers have used the service to quickly and easily build and train machine learning (ML) models and directly deploy them into a production-ready hosted environment. SageMaker notebook instances provide a powerful, integrated Jupyter notebook interface for easy access to data sources for exploration and analysis. You can enhance the SageMaker capabilities by connecting the notebook instance to an Apache Spark cluster running on Amazon EMR . It gives data scientists and engineers a common instance with shared experience where they can collaborate on AI/ML and data analytics tasks. If you’re using a SageMaker notebook instance, you may need a way to allow different personas (such as data scientists and engineers) to do different tasks on Amazon EMR with a secure authentication mechanism. For example, you might use the Jupyter notebook environment to build pipelines in Amazon EMR to transform d

https://cdn-images-1.medium.com/max/1000/0*45Q0tXj4eK5kCX-X Original Source Here Artificial Intelligence: Week #48 | 2020 This week in AI & Machine Learning: Saving animals in the rainforest, rescuing humans, digital twins, AWS re:invent, Very Deep VAE, and more! Hello readers! This post is a few days later than normal due to the holiday, and a much needed long weekend! You can subscribe to our publication on medium to get weekly AI news and more! Photo by Gagandeep Singh on Unsplash Artificial Intelligence News: Last week we talked about saving elephants with machine learning and opencollar . This week we have more cool news about big tech companies working to save endangered animals! Check out how Google is using machine learning to detect gunshots in the rainforest to monitor for illegal poaching activities. Seeing more of these types of projects is so cool. If you’re working on something like this for college or a non profit organization, contact us if you need

Original Source Here Glossary: The Shell is an interpreter that presents the command-line interface to users to let them interact with the kernel . It lets them control the computer using commands entered from a keyboard. It also translates the commands from the programming language into the machine language for the kernel. [ Return ] The Interpreter is a program that reads through programs that are written in human-readable programming languages and executes the instructions from top to bottom. It translates each instruction to a machine language the hardware can understand, executes it, and proceeds to the next instruction. [ Return ] The Command-Line Interface (CLI) is also known as the terminal or console. It’s a program that accepts text input from users to execute commands on the operating system. It lets users configure the computer, install software, and access features that aren’t available in the graphical user interface. [ Return ] The Kernel is the progr

Original Source Here Glossary: The Shell is an interpreter that presents t h e command-line interface to users to let them interact with the kernel . It lets them control the computer using commands entered from a keyboard. It also translates the commands from the programming language into the machine language for the kernel. [ Return ] The Interpreter is a program that reads through programs that are written in human-readable programming languages and executes the instructions from top to bottom. It translates each instruction to a machine language the hardware can understand, executes it, and proceeds to the next instruction. [ Return ] The Command-Line Interface (CLI) is also known as the terminal or console. It’s a program that accepts text input from users to execute commands on the operating system. It lets users configure the computer, install software, and access features that aren’t available in the graphical user interface. [ Return ] The Kernel is the pro

https://news.mit.edu/sites/default/files/styles/news_article__cover_image__original/public/images/202011/MIT-robotgrammar-02-Press.jpg?itok=PxMvzg_e Original Source Here So, you need a robot that climbs stairs. What shape should that robot be? Should it have two legs, like a person? Or six, like an ant? Choosing the right shape will be vital for your robot’s ability to traverse a particular terrain. And it’s impossible to build and test every potential form. But now an MIT-developed system makes it possible to simulate them and determine which design works best. You start by telling the system, called RoboGrammar, which robot parts are lying around your shop — wheels, joints, etc. You also tell it what terrain your robot will need to navigate. And RoboGrammar does the rest, generating an optimized structure and control program for your robot. The advance could inject a dose of computer-aided creativity into the field. “Robot design is still a very manual process,” says Allan Zhao

Original Source Here If not for the guidance of the handful of people I call mentors, I wouldn’t have grown to be a Senior Data Scientist. 90% of the success is all my hard work, but I attribute 10% of that growth to the crucial directions I was guided towards. After graduating, I didn’t know if I had to pursue a M aster’s or a Ph.D. or directly step into the AI industry. When I stepped into the industry, I didn’t know how to best handle work and balance life. When presented with opportunities and responsibilities, I didn’t know how to lead people and handle clients. To achieve every milestone in my career, I learned it from my mentors. And I never went and asked them to mentor me. You never go and ask someone to mentor you. Mentorship happens organically. Mentors spend a minimal amount of time with you while you do 90% of the work. Most mentors wouldn’t even realize they are one. They don’t expect anything in return from you. The world of Data Science isn’t the same as how

Original Source Here How Artificial Intelligence Help Patients Sleep Better Disrupted sleep could delay discharge and recovery. Edited by the author using Canva . Original photo by Buenosia Carol from Pexels . P roblem: Overnight vital sign monitoring cause impaired sleep in patients Poor sleep quality of patients in a hospital is a big issue. Researchers have noted that ~50% of the patients report experiencing insomnia. According to a study done in 2017 [1] , short-term consequences of sleep disruption include: Increased stress responsivity Reduced quality of life Emotional distress Mood disorders Other mental health problems; cognition, memory, and performance deficits Since patients admitted to hospitals already have a compromised immune system, these consequences could be more severe for them. Rest is crucial to a patient’s care. It has been well-documented that disrupted sleep is a common complaint that could delay discharge and recovery.[3] The overnight

Original Source Here Artificial Intelligence predicts 96% of COVID-19 cases requiring intensive care With the use of a new Machine Learning algorithm, it has been possible to detect who is most at risk, helping to discover early who is required to intervene and save lives. Normally, patients with chest scans were only studied to predict severity, looking for lung abnormalities and COVID-19 in 90% of cases. But the current algorithm combines chest scans and data such as demographic information, vital signs, and blood tests. This has been tested with 295 patients, successfully predicting 96% of the cases that required more attention. AI/ML Trending AI/ML Article Identified & Digested via Granola by Ramsey Elbasheer; a Machine-Driven RSS Bot via WordPress https://ramseyelbasheer.wordpress.com/2020/11/29/artificial-intelligence-is-used-to-create-the-first-infinite-video-on-the-internet/

Original Source Here ทำนายประเภทของหนังสือจากหน้าปกด้วย Deep Learning Photo by Brett Jordan on Unsplash เคยสังเกตกันไหมว่าหน้าปกของหนังสือแต่ละประเภทจะมีลักษณะบางอย่างที่คล้าย ๆ กันอยู่ ยกตัวอย่างเช่น การจัดวางหน้า องค์ประกอบหรือการเลือกใช้โทนสี โดยบางครั้งเราก็สามารถรู้ได้ในทันทีที่เห็นหน้าปกของหนังสือว่าหนังสือเล่มนี้เป็นหนังสือประเภทไหน เป็นเพราะว่าเราเคยเห็นหนังสือที่มีลักษณะแบบนี้มาก่อน ซึ่งโปรเจคนี้จะนำเอา Deep learning มาใช้ในการทำนายประเภทของหนังสือ โดยการทดลองให้คอมพิวเตอร์เรียนรู้แพทเทิร์นที่ซ่อนอยู่ในปกหนังสือแต่ละประเภท Dataset ชุดของข้อมูลที่จะนำมาใช้ในการ train model มาจากการทำ Web scraping รูปหน้าปกหนังสือจากเว็บไซต์ naiin.com ซึ่งเหตุผลในการเลือกใช้ข้อมูลจากเว็บไซต์นี้เนื่องจากเป็นร้านหนังสือที่มีข้อมูลของหนังสืออยู่เป็นจำนวนมากและการจัดหมวดหมู่ที่ไม่ซับซ้อน ภาพเว็บไซต์ naiin.com เว็บไซต์ naiin.com ได้ทำการจัดหมวดของหนังสือเป็น 21 หมวด หมวดของหนังสือในเว็บไซต์ naiin.com Web scraping ในการทำ Web scraping เราได้ใช้ library ชื่อ Requests ในการ down