🔥 Enroll for FREE Machine Learning Course & Get your Completion Certificate: https://www.simplilearn.com/learn-machine-learning-basics-skillup?utm_campaign=MachineLearning&utm_medium=DescriptionFirstFold&utm_source=youtube This Machine Learning Algorithms video will help you learn what is Machine Learning, various Machine Learning problems and the algorithms, key Machine Learning algorithms with simple examples and use cases implemented in Python. The key Machine Learning algorithms discussed in detail are Linear Regression, Logistic Regression, Decision Tree, Random Forest and KNN algorithm. Below topics are covered in this Machine Learning Algorithms Tutorial: 00:00 – 03:39 Machine Learning example and real-world applications 03:39 – 04:40 What is Machine Learning? 04:40 – 06:14 Processes involved in Machine Learning 06:14 – 09:40 Type of Machine Learning Algorithms 09:40 – 10:04 Popular Algorithms in Machine Learning 10:04 – 29:10 Linear regression 29:10 – 52:49 Logistic regression 52:49 – 01:04:45 Decision tree and Random forest 01:04:52 – 01:10:28 K nearest neighbor Dataset Link – https://drive.google.com/drive/folders/1FaV91OkTsABJrjnfeeTR4rwLe0mxFHxZ What is Machine Learning? Machine Learning is an application of Artificial Intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Various machine learning algorithms are used to train models that can solve business problems. Linear regression, Logistic regression, Decision tree, Random forest, and K nearest neighbors are some of the popular machine learning algorithms used in the industries. Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Machine-Learning-Algorithms-I7NrVwm3apg&utm_medium=Tutorials&utm_source=youtube Machine Learning [More]

The College of Natural & Agricultural Sciences at the University of California, Riverside is proud to present the 2022 Science Lecture Series entitled Big Data Science. The third of this four-part is Tuesday, April 19, with Dr. Mark Alber, UC Riverside Distinguished Professor of Mathematics, with a presentation on Computational Modeling and Digital Twin of a Patient. Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. This technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where clinicians have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. Multiscale computational modeling is a successful strategy to integrate multiscale, multiphysics data and uncover biological mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large datasets from different sources and different levels of resolution In this lecture, Dr. Alber will demonstrate that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that can provide new insights into disease mechanisms, help identify new targets and patient specific treatment strategies, and inform decision [More]

CENTURY had the pleasure of speaking with Sir Dermot Turing, Alan Turing’s nephew, about Alan’s legacy and how science and AI skills can be fostered in schools. Sir Dermot is the acclaimed author of Prof, a biography of his uncle, The Story of Computing, and most recently X, Y and Z – the real story of how Enigma was broken. Learn more about these and more at https://dermotturing.com/ Learn more about CENTURY, the award-winning AI-powered learning tool, at https://www.century.tech/

Reality behind data science jobs. Is machine learning really cool? 🌎 Website: https://www.skillbasics.com/ 🎥 Codebasics Hindi channel: https://www.youtube.com/channel/UCTmFBhuhMibVoSfYom1uXEg #️⃣ Social Media #️⃣ 🔗 Discord: https://discord.gg/r42Kbuk 📸 Instagram: https://www.instagram.com/codebasicshub/ 🔊 Facebook: https://www.facebook.com/codebasicshub 📱 Twitter: https://twitter.com/codebasicshub 📝 Linkedin (Personal): https://www.linkedin.com/in/dhavalsays/ 📝 Linkedin (Codebasics): https://www.linkedin.com/company/codebasics/ 🔗 Patreon: https://www.patreon.com/codebasics?fan_landing=true ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers’.

7604818524, 9488042210 #ArtificialIntelligence and Robotics | Career in AI | Complete Details Super Smart Artificial Intelligence and the Future | A New Era of Artificial Intelligence How To Become An Artificial Intelligence Engineer | AI Engineer Career Path And Skills How To Become An Artificial Intelligence Engineer | #AIEngineer Career Path And Skills B Tech #ArtificialIntelligenceandData Science in 2021 Higher Studies Career Selection in Tamil Google Free Artificial Intelligence Certification Course | Get Foreign University Certificate Free 🔥Artificial Intelligence Tamil 2018 | Artificial Intelligence இலவசமாக படிக்கலாம் | Tamil #AI jobs vacancy Liked videos SUBSCRIPTIONS B.Tech. in AI & #DataScience AI Certification – Artificial Intelligence Classes Industry Endorsed & Practical Learning via Projects & Case Studies. Meet an Expert Today. Live… Artificial Intelligence and Robotics | Career in AI AI VS ML VS DL VS Data Science #AIMachineLearning Basics | What Is #MachineLearning? | Introduction To Machine Learning |

5 Essential end to end data science projects for a data scientist resume. 3 of these projects are machine learning projects and 2 of them are power bi, tableau dashboarding BI projects. These are end to end data science, machine learning projects that will look very good on your resume. All of these projects are free and available on youtube along with the code. at 11:08 I have discussed important tips to generate new project ideas for data science and machine learning. ***This video is sponsored by Udemy, a popular e-learning platform. Get up to 80% off on your udemy course purchase by using below links, Udemy: https://click.linksynergy.com/fs-bin/click?id=fR6pl33ZVWU&offerid=624447.18009&type=3&subid=0 Here are few courses that I recommend for learning Power BI and Tableau. Power BI Up and Running: https://click.linksynergy.com/fs-bin/click?id=fR6pl33ZVWU&offerid=624447.18011&type=3&subid=0 Complete Power BI Intro: https://click.linksynergy.com/fs-bin/click?id=fR6pl33ZVWU&offerid=624447.18010&type=3&subid=0 Tableau: https://click.linksynergy.com/fs-bin/click?id=fR6pl33ZVWU&offerid=624447.18008&type=3&subid=0 (Note: I earn some affiliate commission when you buy above courses) 🤝 Support my youtube channel by buying a data science, coding 👕 T-shirt: https://kaaipo.com/collections/coding-collection/?utm_source=youtube&utm_medium=post&utm_campaign=codebasics-community ⭐️ Timestamps ⭐️ 00:00 Introduction 00:56 Power BI, Tableau project to generate sales insights 03:09 Power BI project for personal finances 04:28 Machine learning project: Classification 06:20 Machine learning project: Regression 08:58 Deep learning project in Tensorflow 11:08 3 Tips to generate data science project ideas Projects playlists: Sales insights (Power BI): https://www.youtube.com/playlist?list=PLeo1K3hjS3uva8pk1FI3iK9kCOKQdz1I9 Sales insights (Tableau): https://www.youtube.com/playlist?list=PLeo1K3hjS3usDI9XeUgjNZs6VnE0meBrL Personal finance dashboard (Power BI): https://www.youtube.com/watch?v=pqSoCa2NGj4 Classification Project: https://www.youtube.com/playlist?list=PLeo1K3hjS3uvaRHZLl-jLovIjBP14QTXc Regression Project: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7clOTtwsp94PcHbzqpAdg Deep Learning Project: https://www.youtube.com/playlist?list=PLeo1K3hjS3ut49PskOfLnE6WUoOp_2lsD 🎥 Codebasics Hindi channel: https://www.youtube.com/channel/UCTmFBhuhMibVoSfYom1uXEg #️⃣ Social Media #️⃣ 🔗 Discord: https://discord.gg/r42Kbuk 📸 Instagram: https://www.instagram.com/codebasicshub/ 🔊 Facebook: https://www.facebook.com/codebasicshub [More]

The people who own the Dwave video at 45:46 – 46:59 have claimed copyright, so there might be ads. Use adblock 🙂 Occult Mission patches – https://revolutionizingawareness.com Through The Looking Glass …and Beyond – https://youtu.be/2xT6fcm4V1o Predicting The FUTURE To Stop Global Disaster? – https://youtu.be/-fBcMRleHJs A.I., Meditation & “Nonduality” – https://youtu.be/XCYKoINGTHc Sophia and LOVING AI Project – Meditation Session – https://youtu.be/uRq5C-hdhhI Geordie Rose – Quantum Computing: Artificial Intelligence Is Here – https://youtu.be/PqN_2jDVbOU “Christ Consciousness” Debunked By Jesus – https://youtu.be/rjvGYwU6Y6I

As the director of the Strategic Technology Office at the Defense Advanced Research Projects Agency (or DARPA), Timothy leads the office in development of breakthrough technologies to enable war fighters to field, operate, and adapt distributed, joint, multi-domain combat capabilities at continuous speed. He is also founder and president of Fortitude Mission Research LLC and spent several years as a senior intelligence officer with the CIA. Here he illustrates the concept of Mosaic Warfare, in which individual warfighting platforms, just like ceramic tiles in a mosaic, are placed together to make a larger picture. This philosophy can be applied to tackle a variety of human challenges including natural disasters, disruption of supply chains, climate change, pandemics, etc. He also discusses why super AI won’t represent an existential threat in the foreseeable future, but rather an opportunity for an effective division of labour between humans and machines (or human-machine symbiosis). *** Download article from the Scientific Video Protocols website: https://scivpro.com/manuscript/10_32386_scivpro_000024 Scientific Video Protocols is the first full open-access peer-reviewed video journal publishing in 4k cinematic quality. Contact us for submissions: https://scivpro.com/submit/​ *** CONNECT: – Subscribe to this YouTube channel – Support on Patreon: https://www.patreon.com/bullaki – Spotify: https://open.spotify.com/show/1U2Tnvo1PZY4Fu4QLHURJV – Apple Podcast: https://podcasts.apple.com/gb/podcast/bullaki-science-podcast/id1538487175 – LinkedIn: https://www.linkedin.com/in/samuele-lilliu/ – Website: www.bullaki.com – Minds: https://www.minds.com/bullaki/ #bullaki #science #podcast #jadc2 #mosaic #warfare *** Featured in Forbes: https://www.forbes.com/sites/davidhambling/2021/01/29/an-insiders-view-of-darpa-the-worlds-most-advanced-research-agency/?sh=3583332512bb by David Hambling: The Defense Advanced Research Projects Agency, better known as DARPA, has been dubbed the Pentagon’s ‘department of mad science.’ Set up response the Soviet Union’s surprise launch [More]

🔥 Data Science Master Program (Use Code “𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎”): https://www.edureka.co/masters-program/data-scientist-certification This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms. Below are the topics covered in this Data Science for Beginners tutorial video: 00:00 Agenda 2:44 Introduction to Data Science 9:55 Data Analysis at Walmart 13:20 What is Data Science? 14:39 Who is a Data Scientist? 16:50 Data Science Skill Set 21:51 Data Science Job Roles 26:58 Data Life Cycle 30:25 Statistics & Probability 34:31 Categories of Data 34:50 Qualitative Data 36:09 Quantitative Data 39:11 What is Statistics? 41:32 Basic Terminologies in Statistics 42:50 Sampling Techniques 45:31 Random Sampling 46:20 Systematic Sampling 46:50 Stratified Sampling 47:54 Types of Statistics 50:38 Descriptive Statistics 55:52 Measures of Spread 55:56 Range 56:44 Inter Quartile Range 58:58 Variance 59:36 Standard Deviation 1:14:25 Confusion Matrix 1:19:16 Probability 1:24:14 What is Probability? 1:27:13 Types of Events 1:27:58 Probability Distribution 1:28:15 Probability Density Function 1:30:02 Normal Distribution 1:30:51 Standard Deviation & Curve 1:31:19 Central Limit Theorem 1:33:12 Types of Probablity 1:33:34 Marginal Probablity 1:34:06 Joint Probablity 1:34:58 Conditional Probablity 1:35:56 Use-Case 1:39:46 Bayes Theorem 1:45:44 Inferential Statistics 1:56:40 Hypothesis Testing 2:00:34 Basics of Machine Learning 2:01:41 Need for Machine Learning 2:07:03 What is Machine Learning? 2:09:21 Machine Learning Definitions 2:!1:48 Machine Learning Process 2:18:31 Supervised Learning Algorithm 2:19:54 What is Regression? 2:21:23 Linear vs Logistic Regression 2:33:51 Linear Regression 2:25:27 [More]

Mathias Ekman from Microsoft speaks about the future of Life science powered by AI and Genomics. #pharma #ai #science #genomics #conference #dubrovnik #pharmaceuticals #panel #future #learning #talks #keynote Get your tickets for this NEXT 2021 event now: https://nextpharmasummit.com

Science Documentary: Artificial Intelligence, Cloud Robots, Trusting Technology As technology advances, a portion of our population cannot help but react with panic. Throughout our human history, as technology grows, so to has our fear as to where this technology will take us. This fear has taken hold through each and every stage of the industrial revolution. Fears such that, the alphabet will wipe away our memories, the telegraph will stop us from remembering how to write in full sentences. But the closer the technology resembles us humans, as in robotics and artificial intelligence, the greater is our fear. Yet if we build robots in the image that we wish for us to be, then the future of technology is sure to be an exciting one. Cloud Robots Computers can only answer questions posed by the humans who programmed them. So it is up to humans to ask the truly important questions. Is it possible for machines to make better decisions than humans? Several top tech company CEO’s have advised about the concerns they have about the singularity. But now there is a new idea, called the multiplicity, in which diverse groups of humans work together with diverse groups of machines, with the goal to ultimately be making the very best decisions. Computers and machines have the advantage over humans in their speed and precision. We rely on them in our everyday lives, with things like pace makers and auto pilot systems. And now many Institutions studying computer science are putting [More]

A realistic look in the future of AI Dr. Julie Carpenter will talk about the fears and hopes that the topic of artificial intelligence evokes in people. She will correct false impressions, discuss the implications of this topic in the here and now, and take a realistic look at the future. Finally, she will also address ethical issues in this context. She takes a critical and very pragmatic look at the future of AI. Dr. Julie Carpenter https://www.jgcarpenter.com TW: https://twitter.com/jgcarpenter

If you have ever been wracked with indecision over seemingly simple tasks, such as what clothes to wear that day or which restaurant to choose for dinner, then Cognitive and Computer Scientist, Tom Griffiths has the solution – there’s an algorithm for that. In this talk, he offers practical solutions to problems as well as a different way to think about rational decision-making and argues that human choices can be made easier with computer science. Tom Griffiths is a Professor of Psychology and Cognitive Science at the University of California, Berkeley, where he is also the Director of the Institute of Cognitive and Brain Sciences. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life. Tom was an undergraduate at the University of Western Australia, completed his PhD in Psychology at Stanford University in 2005, and taught at Brown University before moving to Berkeley. He has received early career awards for his research from the United States National Science Foundation, the Sloan Foundation, the Society for Mathematical Psychology, the Society for Experimental Psychology, the Association for Psychological Science, and the American Psychological Association. In 2016, Tom and his friend and collaborator Brian Christian published _Algorithms to live by_, introducing ideas from computer science and cognitive science to a general audience and illustrating how they can be applied to human decision-making. The book was named as one of the Amazon.com “Best [More]

One important topic for the field of machine learning is fairness in AI, which has become a table-stake for ML platforms and services, driven by customer / business needs, regulatory / legal requirements and societal expectations. Researchers have been actively studying how to address disparate treatment caused by bias in the data and the resulting amplification of such bias by ML models, and how to ensure that the learned model does not treat subgroups in the population unfairly. During NeurIPS 2020, five Amazon scientists working on these types of challenges gathered for a 45-minute virtual session to address the topic. Watch the recorded panel discussion here, where the scientists discuss how fairness applies to their areas of AI / ML research, the interesting studies and advancements happening in the space, and the collaborations they’re most excited to see occurring across the industry in an effort to advance fairness in AI. Learn more: https://www.amazon.science/videos-webinars/amazon-panel-to-host-virtual-event-on-fairness-in-ai Follow us: Twitter: https://twitter.com/AmazonScience Facebook: https://www.facebook.com/AmazonScience Instagram: https://www.instagram.com/AmazonScience LinkedIn: https://www.linkedin.com/showcase/AmazonScience Newsletter: https://www.amazon.science/newsletter

In our SERIES FINALE of Crash Course Computer Science we take a look towards the future! In the past 70 years electronic computing has fundamentally changed how we live our lives, and we believe it’s just getting started. From ubiquitous computing, artificial intelligence, and self-driving cars to brain computer interfaces, wearable computers, and maybe even the singularity there is so much amazing potential on the horizon. Of course there is also room for peril with the rise of artificial intelligence and more immediate displacement of much of the workforce through automation. It’s tough to predict how it will all shake out, but it’s our hope that this series has inspired you to take part in shaping that future. Thank you so much for watching. Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios Want to know more about Carrie Anne? https://about.me/carrieannephilbin The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list=PL1mtdjDVOoOqJzeaJAV15Tq0tZ1vKj7ZV Want to find Crash Course elsewhere on the internet? Facebook – https://www.facebook.com/YouTubeCrash… Twitter – http://www.twitter.com/TheCrashCourse Tumblr – http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids

Parkinson’s disease (PD) is a progressive disorder with a presymptomatic interval; that is, there is a period during which the pathologic process has begun, but motor signs required for the clinical diagnosis are absent. There is considerable interest in discovering markers to diagnose this preclinical stage. Current predictive marker development stems mainly from two principles; first, that pathologic processes occur in lower brainstem regions before substantia nigra involvement and second, that redundancy and compensatory responses cause symptoms to emerge only after advanced degeneration. Decreased olfaction has recently been demonstrated to predict PD in prospective pathologic studies, although the lead time may be relatively short and the positive predictive value and specificity are low. Screening patients for depression and personality changes, autonomic symptoms, subtle motor dysfunction on quantitative testing, sleepiness and insomnia are other potential simple markers. More invasive measures such as detailed autonomic testing, cardiac MIBG-scintigraphy, transcranial ultrasound, and dopaminergic functional imaging may be especially useful in those at high risk or for further defining risk in those identified through primary screening. Despite intriguing leads, direct testing of preclinical markers has been limited, mainly because there is no reliable way to identify preclinical disease. Idiopathic RBD is characterized by loss of normal atonia with REM sleep. Approximately 50% of affected individuals will develop PD or dementia within 10 years. Dataset Link: https://archive.ics.uci.edu/ml/datasets/parkinsons #machinelearning #artificialintelligence #ai #datascience #python #programming #technology #deeplearning #coding #bigdata #computerscience #tech #data #pythonprogramming #programmer #developer #dataanalytics #software #datascientist #javascript #iot #java #coder #ml #innovation #robotics #linux #analytics [More]

Great Learning cordially invites you to be a part of the online launch event of IIIT-Delhi’s Post Graduate Diploma in Computer Science and Artificial Intelligence. The program will be launched in the presence of IIIT Delhi and Great Learning dignitaries, who’ll be sharing their valuable insights on how this program focussed on emerging technologies will help shape our futures. The panelists include: 𝗜𝗜𝗜𝗧-𝗗𝗲𝗹𝗵𝗶 𝗙𝗮𝗰𝘂𝗹𝘁𝘆: ● Prof. Sanjit Krishnan Kaul – Professor, ECE Department, Program Coordinator, PG Diploma in Computer Science & AI, IIIT Delhi ● Prof. Saket Anand – Head, Infosys Center for Artificial Intelligence (CAI), IIIT-Delhi and Associate Professor (CSE, ECE), IIIT-Delhi ● Prof. Raghava Mutharaju – Associate Professor, CSE IIIT Delhi 𝗚𝗿𝗲𝗮𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗧𝗲𝗮𝗺: ● Harish Subramanian – Director, Academics & New Products, Great Learning ● Mohan Lakhamraju – Founder & CEO, Great Learning Key questions that will get answered: How would the program help candidates become future-ready and build rewarding careers? Who is this program for? What roles can participants aspire for? What are the key learning outcomes from the programs?” About Great Learning: – Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more.

Wish to build your career in Data Science and Artificial Intelligence space? Here is a video with the best advice from subject matter experts. Listen to these data scientists share tips on how to crack a data science interview or an artificial intelligence interview along with advice on how to make a career transition into AI, Machine Learning and Data Science. You will also find tips on how to build an effective resume. 0:33 AI Career Advice from Swiggy Data Scientist 2:12 Data Science Career Advice from Youplus Data Scientist 3:35 Data Science Career Advice from Flipkart Data Scientist 4:38 DS and AI Career Advice from K-Mart Data Scientist 6:09 Data Science Career Advice from Walmart Labs Data Scientist Subscribe to our channel to get updates on the latest videos. Hit the subscribe button now! http://bit.ly/36DfiCy Who is data science for? http://bit.ly/33M0a2T What are the required skills for data science? http://bit.ly/2qnTFFY What does Machine Learning Engineer do? http://bit.ly/2Yeewry Who are we? Springboard is an online learning platform that helps you master in-demand skills through a personal 1:1 mentor-led model and a project-driven curriculum. Over the last 6+ years, we have served 10K+ learners in 100+ countries. We are now in India and are offering Career Track programs in Data Science, Data Analytics and AI/ML along with job guarantee. Apply here: http://bit.ly/34JJt9D For more information, please write to us at india@springboard.com or call us at +91 8098866488 or +91 7483024694 Follow Springboard: Facebook: https://www.facebook.com/springboardind/ LinkedIn: https://www.linkedin.com/company/spri Twitter: https://twitter.com/springboard_ind Medium: https://medium.com/@springboard_ind #DataScience [More]

Watch Rachel Thomas’s talk, “How to Learn Deep Learning (When You’re Not a Computer Science PhD)” from the free, live online Demystifying Data Science conference hosted by Metis on September 27, 2017. Rachel Thomas has a math Ph.D. from Duke and was selected by Forbes as one of “20 Incredible Women Advancing AI Research”. She is co-founder of fast.ai and a researcher-in-residence at the University of San Francisco Data Institute. Her background includes working as a quant in energy trading, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright.

👉 Download Our Free Data Science Career Guide:✅https://bit.ly/31XjqMw 👉 Sign up for Our Complete Data Science Training:✅https://bit.ly/3mqEBzW So, you want to become a data scientist? Great! Our free step by step guide will walk you through how to start a career in data science: https://bit.ly/31XjqMw ** Expand for some additional INFO and LINKS ** Data science consulting companies are a hot choice if you’re looking for a job in the field. They offer numerous development opportunities, access to the latest technologies, and provide data-based solutions for top-notch companies across the globe. Furthermore, on top of generous salaries, they seem to have tons of cool perks – from unlimited vacation days and free meals to hair salons and masseuses on site. This doesn’t make your choice any simpler, though. With so many industries and companies out there, it’s hard to keep track of who-offers-what-and-where. So, watch this video to find out which companies provide the best overall employee experience! Complete Data Science Online Training Program. Earn a data science degree at your own pace. Sign up here: https://bit.ly/3mqEBzW Follow us on YouTube: ✅https://www.youtube.com/c/365DataScience Connect with us on our social media platforms: ✅Website: http://bit.ly/2TNHi0B ✅Facebook: https://www.facebook.com/365datascience ✅Instagram: https://www.instagram.com/365datascience ✅Q&A Hub: https://365datascience.com/qa-hub/ ✅LinkedIn: https://www.linkedin.com/company/365datascience Prepare yourself for a career in data science with our comprehensive program: ✅https://bit.ly/3mqEBzW Get in touch about the training at: support@365datascience.com Comment, like, share, and subscribe! We will be happy to hear from you and will get back to you! #data #science #companies #career #firms #scientist

Happy Passover wishing you the robots of the R&D Institute for Intelligent Robotic Systems CS Department, College of Management Academic Studies, ISRAEL. http://www.colman.ac.il. This institute was funded by the parents of the three IDF soldiers, in memory of their sons, Benny Avraham, Adi Avitan, and Omer Souad, kidnapped and murdered by Hezbollah in 2000. The Institute was inaugurated in June 2008, and is currently engaged in developing autonomous robotic systems to identify and handle suspicious objects as well as in developing autonomous robotic mapping, delivery and entertainment systems. Background music: Ma Nishtana. Lyrics from the Haggadah, traditional music. Performed by Tom Rahav and Matan Ariel. Musical Arrangement: Noam Zlatin. Recording: Esta Studios, February 2002. The use of the recording for this specific video is authorized by Matan Ariel & Friends (http://www.MatanArielAndFriends.com). מוזיקת רקע: מה נשתנה. מילים מן ההגדה, לחן מסורתי. ביצוע: תום רהב ומתן אריאל. עיבוד מוזיקלי, ניהול מוזיקלי ונגינה: נעם זלטין. הוקלט באולפני אסטה, פברואר 2002. השימוש בהקלטה בווידאו זה באישור מתן אריאל וחברים (http://www.MatanArielAndFriends.com).

A panel at the “Web We Want” festival, May 2015 at the Southbank Centre, London. The video was broadcast via Periscope – hence the quality, and is used by kind permission of the WebWeWant Festival, SouthBank Centre and organisers ANXS Collective

Today we’re going to talk about how computers understand speech and speak themselves. As computers play an increasing role in our daily lives there has been an growing demand for voice user interfaces, but speech is also terribly complicated. Vocabularies are diverse, sentence structures can often dictate the meaning of certain words, and computers also have to deal with accents, mispronunciations, and many common linguistic faux pas. The field of Natural Language Processing, or NLP, attempts to solve these problems, with a number of techniques we’ll discuss today. And even though our virtual assistants like Siri, Alexa, Google Home, Bixby, and Cortana have come a long way from the first speech processing and synthesis models, there is still much room for improvement. Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios Want to know more about Carrie Anne? https://about.me/carrieannephilbin The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list=PL1mtdjDVOoOqJzeaJAV15Tq0tZ1vKj7ZV Want to find Crash Course elsewhere on the internet? Facebook – https://www.facebook.com/YouTubeCrash… Twitter – http://www.twitter.com/TheCrashCourse Tumblr – http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids

Talk by Ekaterina Kochmar, University of Cambridge, at the Cambridge Coding Academy Data Science Bootcamp: https://cambridgecoding.com/datascience-bootcamp