Check out How Artificial Intelligence Can Change The Health Care Industry Future. AIBridge ML has been contributing to innovation and advanced research in Artificial Intelligence by working with a pool of resources well-versed in learning models and languages that are used in coding intelligent bots and assistants. Our team is capable of understanding client requirements to develop best-in-class AI solutions that can fulfill client requirements in addition to consulting and support services around Artificial Intelligence. Contact us: for Artificial Intelligence Solutions. โ˜Ž๏ธ +91 40 4640 0400 ๐Ÿ’ป โœ‰๏ธ
In this video, Dr. Webb talks about artificial intelligence and whether this will be the future of medicine. Articles can be found here: Click below to be added to Dr. Webb’s email list to be the first to be notified about what he is up to, pre-med and medical school advice, and general tips to be successful Dr. Webb’s Amazon Shopping List and Personal Recommendations: Looking for a more personalized and 1:1 mentorship with Dr. Webb to help you reach your goals, then look no further! Become a patreon and receive weekly or monthly phone calls from Dr. Webb, opportunity to have your application or personal statement reviewed, access to exclusive behind the scenes footage with never released pre-med/med/residency videos, personalized and proven to work study plans for the MCAT, USMLE step 1,2,and 3, and the chance to network with a physician in your career of choice plus more! Become a patreon TODAY! Visit: Book I Used to Do Well in Medical School Constanza Physiology: Pathoma: USMLE Step 1 First Aid: BRS Physiology: BRS Biochemisry: BRS Gross Anatomy: BRS Cell Biology: BRS Pathology: BRS Microbiology: BRS Pharmacology: BRS Embryology: Items I Used to Work Out and Stay Healthy in Medical School Harbinger Pro Wristwrap Weightlifting Gloves: Beats Studio Wireless Over-Ear Headphone (Matte Black) BlenderBottle Classic Loop Top Shaker Bottle: Under Armour Men’s Muscle Tank: Under Armour Men’s Maverick Tapered Pants: [More]
What is A.I? Why is Elon Musk worried about it? Can it be smarter than us? What can we do to prevent a doomsday? How to get people more serious about it? What are the latest trends? Will AI be good or bad? How can we use it? Who will lose their jobs, what’s the solution? Will we ourselves become AI? Will we shed our biological limbs for a better alternative?
As sophisticated algorithms can complete tasks we once thought impossible, computers are seeming to become a real threat to humanity. Subscribe to The Guardian โ–บ Whether they decide to pulp us into human meat paste, or simply make our work completely unnecessary, argues technology reporter Alex Hern, we should be afraid of computers. Guardian website โ–บ Suggested videos: The last job on Earth โ–บ Capitalism is failing โ–บ Guardian playlists: Comment is Free โ–บ Guardian Docs โ–บ Guardian Features โ–บ Guardian Animations & Explanations โ–บ Guardian Investigations โ–บ The Global Migration Crisis โ–บ Anywhere but Westminster โ–บ Casetteboy remix the news โ–บ More Guardian videos: We Walk Together โ–บ Everyday racism – Akala โ–บ Pretty Radical โ–บ Capitalism is failing – Paul Mason โ–บ My life as a female bodybuilder โ–บ After Banksy: the parkour guide to Gaza โ–บ If I Die On Mars โ–บ Revenge Porn: Chrissy Chambers and her search for justice โ–บ Mos Def force fed in Gitmo procedure โ–บ Edward Snowden interview โ–บ Bangladeshi Sex Workers take steroids โ–บ Other Guardian channels on YouTube: Guardian Football โ–บ Guardian Music โ–บ Guardian Australia โ–บ Guardian Tech โ–บ Guardian Culture โ–บ Guardian Wires โ–บ Guardian Food โ–บ
Full episode with Nick Bostrom (Mar 2020): Clips channel (Lex Clips): Main channel (Lex Fridman): (more links below) Podcast full episodes playlist: Podcasts clips playlist: Podcast website: Podcast on Apple Podcasts (iTunes): Podcast on Spotify: Podcast RSS: Nick Bostrom is a philosopher at University of Oxford and the director of the Future of Humanity Institute. He has worked on fascinating and important ideas in existential risks, simulation hypothesis, human enhancement ethics, and the risks of superintelligent AI systems, including in his book Superintelligence. I can see talking to Nick multiple times on this podcast, many hours each time, but we have to start somewhere. Subscribe to this YouTube channel or connect on: – Twitter: – LinkedIn: – Facebook: – Instagram: – Medium: – Support on Patreon:
We are in a simulation. Has it occurred to you that means God is real? By drawing parallels to worlds we have created, we ask, from inside our simulator, what actions do we have available? Can we get out? Meet God? Kill him? About SXSW: SXSW dedicates itself to helping creative people achieve their goals. Founded in 1987, SXSW is best known for its conference and festivals that celebrate the convergence of the interactive, film, and music industries. An essential destination for global professionals, the event features sessions, showcases, screenings, exhibitions, and a variety of networking opportunities. SXSW proves that the most unexpected discoveries happen when diverse topics and people come together. SXSW 2019 takes place every March in Austin, Texas. Subscribe: Connect with SXSW: Website: Facebook: Twitter: Instagram: YouTube:
Top Artificial Intelligence AI Predictions for 2021 In 2019, IDC predicted growth in AI technology, stating that spending on AI tech would increase over two and a half times, amounting to$97.9billion by 2023. Considering the tech and newest inventions in 2019, it is only right that AI flourished even better in 2020. Unfortunately, the coronavirus hit the following year. The global outbreak led to overcrowded hospitals and numerous loss of lives. Significantly, the pandemic accelerated the growth of AI. Despite the pandemic wreaking global havoc, it only minimized the evolution of AI. Many believe AI Stigmatization is a myth, and rightfully so. Although the pandemic slowed down the growth of new AI, it became widely used in arguably every sector in the world. Director of ISG automation Wayne Butterfield said, โ€˜As the grip of the pandemic continues to affect the ability of the enterprise to operate, AI in many guises will become increasingly important as businesses seek to understand their COVID- affected data sets and continue to automate day-to-day tasks.โ€™ 2020 also witnessed more digitally connected business through AI because of the work-from-home policy implemented in almost every country. This trend will undoubtedly continue in 2021. But what other trends are we likely to witness in 2021? Nice to have you back on the channel, guys! Today, we are going to do a quick rundown on the Top artificial intelligence predictions for 2021. Make sure you like, share, comment, and if youโ€™re watching us for the first time, kindly subscribe. [More]
Video games can be tough, but it’s always nice to know that these guys have got your back. Join as we count down our picks for the Top 10 Most Helpful A.I Companions In Video Games. Suggestion Toolโ–บโ–บ Subscribeโ–บโ–บ Facebookโ–บโ–บ Twitterโ–บโ–บ Instagramโ–บโ–บ Channel Pageโ–บโ–บ For this list, we are looking at sidekicks, teammates and partners that accompany the player throughout the experience, helping them to overcome obstacles and enemies, but most importantly are rarely in the way. Special thanks to our user W-S for submitting the idea on our interactive suggestion tool: Check out the voting page here, Want a WatchMojo cup, mug, t-shirts, pen, sticker and even a water bottle? Get them all when you order your MojoBox gift set here: WatchMojo is a leading producer of reference online video content, covering the People, Places and Trends you care about. We update DAILY with 4-5 Top 10 lists, Origins, Biographies, Versus clips on movies, video games, music, pop culture and more!
***AI and Deep Learning using TensorFlow: *** This Edureka Live video on “Tensorflow Image Classification” will provide you with a comprehensive and detailed knowledge of Image classification and how it can be implemented using Tensorflow. It covers the following topics: 1:04 What is TensorFlow 1:35 Applications of TensorFlow 2:32 Image Classification 3:15 Fashion MNIST 16:42 CIFAR-10 ———————————————————– Machine Learning Podcast – Complete Youtube Playlist here: Deep Learning Blog Series: Subscribe to our channel to get video updates. Hit the subscribe button above: Instagram: Slideshare: Facebook: Twitter: LinkedIn: ———————————————————– #edureka #edurekadeeplearning #tensorflow #imageclassification #deeplearning #tensorflowtutorial About the course: Edureka’s Deep Learning in TensorFlow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies. —————————————————— Objectives: Deep Learning in TensorFlow with Python Training is designed by industry experts to make you a Certified Deep Learning Engineer. The Deep Learning in TensorFlow course offers: In-depth knowledge of Deep Neural Networks Comprehensive knowledge of various Neural Network architectures such as Convolutional Neural Network, Recurrent Neural Network, Autoencoders Implementation of Collaborative Filtering with RBM The exposure to real-life industry-based projects which will be executed using TensorFlow library Rigorous involvement of an SME throughout the AI & Deep Learning Training to learn industry [More]
In this video, we will learn How to extract text from a pdf file in python NLP. Natural Language Processing (NLP) is the field of Artificial Intelligence, where we analyse text using machine learning models. Text Classification, Spam Filters, Voice text messaging, Sentiment analysis, Spell or grammar check, Chatbot, Search Suggestion, Search Autocorrect, Automatic Review, Analysis system, Machine translation are the applications of NLP. This notebook demonstrates the extraction of text from PDF files using python packages. Extracting text from PDFs is an easy but useful task as it is needed to do further analysis of the text. We are going to use PyPDF2 for extracting text. You can download it by running the command given below. We have used the file NLP .pdf in this notebook. The open() function opens a file and returns it as a file object. rb opens the file for reading in binary mode. ๐Ÿ”Š Watch till last for a detailed description 02:43 Importing the libraries 06:21 Reading and extracting the data 09:17 Append write or merge PDFs 13:20 Analysing the output ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ โœ๏ธ๐Ÿ†๐Ÿ…๐ŸŽ๐ŸŽŠ๐ŸŽ‰โœŒ๏ธ๐Ÿ‘Œโญโญโญโญโญ ENROLL in My Highest Rated Udemy Courses to ๐Ÿ”‘ Unlock Data Science Interviews ๐Ÿ”Ž and Tests ๐Ÿ“š ๐Ÿ“— NLP: Natural Language Processing ML Model Deployment at AWS Build & Deploy ML NLP Models with Real-world use Cases. Multi-Label & Multi-Class Text Classification using BERT. Course Link: ๐Ÿ“Š ๐Ÿ“ˆ Data Visualization in Python Masterclass: Beginners to Pro Visualization in matplotlib, Seaborn, Plotly & Cufflinks, EDA on Boston Housing, Titanic, IPL, FIFA, [More]
In this video we will see CV and resume parsing with custom NER training with SpaCy. Natural Language Processing (NLP) is the field of Artificial Intelligence, where we analyse text using machine learning models. Text Classification, Spam Filters, Voice text messaging, Sentiment analysis, Spell or grammar check, Chat bot, Search Suggestion, Search Autocorrect, Automatic Review, Analysis system, Machine translation are the applications of NLP. ๐Ÿ”Š Watch till last for a detailed description 02:14 what is Resume summarization? 13:56 Loading the data 25:26 Load the model 34:32 Analysing output ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ โœ๏ธ๐Ÿ†๐Ÿ…๐ŸŽ๐ŸŽŠ๐ŸŽ‰โœŒ๏ธ๐Ÿ‘Œโญโญโญโญโญ ENROLL in My Highest Rated Udemy Courses to ๐Ÿ”‘ Unlock Data Science Interviews ๐Ÿ”Ž and Tests ๐Ÿ“š ๐Ÿ“— NLP: Natural Language Processing ML Model Deployment at AWS Build & Deploy ML NLP Models with Real-world use Cases. Multi-Label & Multi-Class Text Classification using BERT. Course Link: ๐Ÿ“Š ๐Ÿ“ˆ Data Visualization in Python Masterclass: Beginners to Pro Visualization in matplotlib, Seaborn, Plotly & Cufflinks, EDA on Boston Housing, Titanic, IPL, FIFA, Covid-19 Data. Course Link: ๐Ÿ“˜ ๐Ÿ“™ Natural Language Processing (NLP) in Python for Beginners NLP: Complete Text Processing with Spacy, NLTK, Scikit-Learn, Deep Learning, word2vec, GloVe, BERT, RoBERTa, DistilBERT Course Link: . ๐Ÿ“ˆ ๐Ÿ“˜ 2021 Python for Linear Regression in Machine Learning Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal. You will learn how to build a Linear Regression model from scratch. Course Link: ๐Ÿ“™๐Ÿ“Š 2021 R 4.0 Programming for Data Science || Beginners to Pro Learn Latest [More]
In this spaCy tutorial, you will learn all about natural language processing and how to apply it to real-world problems using the Python spaCy library. ๐Ÿ’ป Course website with code: โœ๏ธ Course developed by Dr. William Mattingly. Check out his channel: โญ๏ธ Course Contents โญ๏ธ โŒจ๏ธ (0:00:00) Course Introduction โŒจ๏ธ (0:03:56) Intro to NLP โŒจ๏ธ (0:11:53) How to Install spaCy โŒจ๏ธ (0:17:33) SpaCy Containers โŒจ๏ธ (0:21:36) Linguistic Annotations โŒจ๏ธ (0:45:03) Named Entity Recognition โŒจ๏ธ (0:50:08) Word Vectors โŒจ๏ธ (1:05:22) Pipelines โŒจ๏ธ (1:16:44) EntityRuler โŒจ๏ธ (1:35:44) Matcher โŒจ๏ธ (2:09:38) Custom Components โŒจ๏ธ (2:16:46) RegEx (Basics) โŒจ๏ธ (2:19:59) RegEx (Multi-Word Tokens) โŒจ๏ธ (2:38:23) Applied SpaCy Financial NER ๐ŸŽ‰ Thanks to our Champion and Sponsor supporters: ๐Ÿ‘พ Wong Voon jinq ๐Ÿ‘พ hexploitation ๐Ÿ‘พ Katia Moran ๐Ÿ‘พ BlckPhantom ๐Ÿ‘พ Nick Raker ๐Ÿ‘พ Otis Morgan ๐Ÿ‘พ DeezMaster ๐Ÿ‘พ AppWrite — Learn to code for free and get a developer job: Read hundreds of articles on programming: And subscribe for new videos on technology every day:
This talk will introduce participants to the theory and practice of machine learning in production. The talk will begin with an intro on machine learning models and data science systems and then discuss data pipelines, containerization, real-time vs. batch processing, change management and versioning. As part of this talk, an audience will learn more about: โ€ข How data scientists can have the complete self-service capability to rapidly build, train, and deploy machine learning models. โ€ข How organizations can accelerate machine learning from research to production while preserving the flexibility and agility of data scientists and modern business use cases demand. A small demo will showcase how to rapidly build, train, and deploy machine learning models in R, python, and Spark, and continue with a discussion of API services, RESTful wrappers/Docker, PMML/PFA, Onyx, SQLServer embedded models, and lambda functions.
If you want to do machine learning and are looking for a new computer stop. Do not buy one, just use google colab. 3 Data Science Learning Platforms I would recommend 1. Data Quest – (my favourite) 2 Data Camp – 3 365 Data Science – 2 Recommended Python Courses 1. Exploratory Data Analysis with Python and Pandas – 2. Complete Python Programmer Bootcamp – Data Science Interview Preparation StrataScratch (These contain affiliate links, which means I receive a percentage of any sales made. There is no additional cost for anybody clicking on them) My favourite books (affiliate link) ๐Ÿ‘Œ SUBSCRIBE to ME!๐Ÿ‘Œ
Welcome to our event celebrating the launch of Machine Learning Engineering for Production (MLOps) Specialization featuring AI leaders in MLOps. Topics we plan to cover: -To what extent does the role of Data Scientist or MLE involve MLOps? -How is MLOps actually implemented in an industry setting? Is there some kind of a framework people use? -Is MLOps suitable for early-stage startups or only teams with enough resources as the big tech companies do? -The latest trends on MLOps and how will the future of it evolve. -What do you see as the biggest challenges for MLOps adoption? -Apart from taking courses, what are some of the other resources or activities might recommend to learners interested in gaining practical experience with MLOps? Speakers: -Andrew Ng, Founder, DeepLearning.AI -Robert Crowe, TensorFlow Developer Engineer, Google -Laurence Moroney, AI Advocate, Google -Chip Huyen, Adjunct Lecturer, Stanford University -Rajat Monga, co-founder, Stealth Startup; Former lead of TensorFlow, Google -Event moderator: Ryan Keenan, Director of Product, DeepLearning.AI Let us know what you think of the event by filling out a quick survey here: To learn more about DeepLearning.AI and sign up for future events: To sign up for Machine Learning Engineering for Production (MLOps),
This video demostrates the creation of of Topic(workflow) in Virtual Agent Designer. As well as, explanation of the Designer tools and utilities. For activating and basic overview of Virtual Agent please refer below link:
In this video I show how easy it is to create a Power Virutal Agent (BOT) and handoff to a human agent using Omnichannel for Customer Service within Dynamics 365.
Cybersecurity vignette with CB Insights analyst Will Altman. Recorded June 20, 2018 at the Future of Fintech Conference.
In this video I show how to extract a malicious URL from a PDF without opening it, how to spot a weaponized Office document, and a method to quickly de-obfuscate PowerShell. Enjoy! Links: – REMnux: – PDF: – Macro-enabled doc: === My SANS Courses: – SEC450 – Blue Team Fundamentals: – MGT551 – Building and Leading Security Operations Centers: PDF Guide to Security Operations: Blueprint Podcast: Twitter:
Our nationโ€™s economy and security depend on a healthy functioning of cyberspace โ€“ the space where almost everything that facilitates our way of life occurs โ€“ from agriculture, water treatment, and telecommunications, to emergency services and the defense industrial base, plus so much more. The United Statesโ€™ future cyber warriors and leaders must be prepared to operate in cyberspace โ€“ the new battlefield. To prepare them, the National Security Agency annually hosts the NSA Cyber Exercise โ€“ a three-day competition that educates, trains, and tests our future cyber warriors and leaders to defend our Nationโ€™s cyber networks. In 2019, cadets and midshipmen from the US. Service Academy at West Point, the US Naval Academy, the US Air Force Academy, the US Coast Guard Academy, and the Merchant Marine Academy. Each team competed in a series of simulated and scored scenarios, but only one academy walked away with the coveted National Security Agencyโ€™s Directorโ€™s Trophy.
Presented at the Matroid Scaled Machine Learning Conference 2018 | #scaledmlconf
Screening and Panel Discussion on Coded Bias Film, March 29 ACM’s Technology Policy Council and Diversity and Inclusion Council sponsored a free screening and public discussion of the film “Coded Bias” and how those in computer science fields can address issues of algorithmic fairness. The discussion occured on Monday, March 29, 2021 from 2:30-4:00 pm EDT (8:30pm CEST). PANELISTS: Dame Prof. Wendy Hall, Regius Professor of Computer Science, University of Southampton Hon. Bernice Donald, Federal Judge U.S. Court of Appeals for the Sixth Circuit Prof. Latanya Sweeney, Daniel Paul Professor of Government & Technology, Harvard University Prof. Ricardo Baeza-Yates, Research Professor, Institute for Experiential AI, Northeastern University MODERATOR: Prof. Jeanna Matthews, Professor of Computer Science, Clarkson University SPONSORS: ACM Technology Policy Council ACM Diversity & Inclusion Council National Science Foundation ADVANCE Grant Clarkson Open Source Institute (COSI), Clarkson University
Unfortunately there was a technical problem and the first part of the panel wasn’t recorded. Our deep apologies! Panel Discussion on the Relationship of AI & Robotics The views of Peter Hart and James Kuffner will differ in many regards. These differences will serve as the starting point for a high-caliber panel discussion. In addition to the two keynote speakers, the panel includes the greats of robotics, vision, and AI: Nils Nilsson, together with Peter Hart, was part of the Shakey project and has an early leader in AI; he continues to write monographs, including some of the earliest textbooks on AI. Ruzena Bajcsy is one of the early visionaries at the intersection of robotics and vision, having pioneered the active vision paradigm, among many other things. Rodney Brooks, the inventor of the subsumption architecture, has caused shifts of tectonic proportions in robotics, both in academia and in industry. He has greatly affected the development of robotics over the last thirty years. Manuela Veloso and Ben Kuipers both are current prolific and recognized leaders who successfully run research endeavors at the intersection of robotics and AI; they will be able to provide today’s perspective on both fields. The panel will be moderated by the IEEE RAS president, Raja Chatila. The year 2015 marks the 50th anniversary of the Shakey project. Conducted at the Stanford Research Institute (now SRI), this project in many ways paved the way for today’s research in robotics and AI. Many accomplishments of this project are still [More]
Panelists include Russ Altman, Justine Cassell, Fernanda Viรฉgas, and Bob Zhang.