github link: https://github.com/krishnaik06/Gender-Recognition-and-Age-Estimator weights: https://drive.google.com/file/d/12Ub2ZUtiYXL1QKUPlAy6oOG4Qhn0GM0H Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici Discord Server Link: https://discord.gg/tvAJuuy Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
Android has an inbuilt feature speech to text through which you can provide speech input to your app. With this feature you can add some of the cool features to your app like adding voice navigation and it is very helpful when you are targeting disabled people. In the background how voice input works is, the speech input will be streamed to a server, on the server voice will be converted to text and finally text will be sent back to our app. Other tutorials : 1) Create a custom AVD :https://youtu.be/Cg7BVTk6r5E 2) Basic Android App :http://youtu.be/q98NC73LEgI 3) Calculator App :https://youtu.be/mrjOLG2Grt0 4) How to create a new activity :https://youtu.be/-xljI2_TRZg 5) How to create a login form :https://youtu.be/x6jQAaLz1O8 Find me here : Tumblr : https://www.tumblr.com/blog/priyanka0304 Google+ : https://plus.google.com/u/0/b/105970252005982916681/105970252005982916681/posts Twitter : https://twitter.com/AndroidAcademy1 Facebook : https://www.facebook.com/AndroidAcademy8?ref=hl
Can you predict the Bitcoin Price with Machine Learning? It seems like it’s possible! Using an LSTM algorithm, I showcase how you can use machine learning to predict prices of cryptocurrencies. Machine Learning can most definitely be used as a support in your bitcoin investing, and as a predictor of the price of cryptocurrencies. Find the code at: https://github.com/OscarAlsingCommunity/Predict-Cryptocurrency-Price-With-Machine-Learning Resources: http://colah.github.io/posts/2015-08-Understanding-LSTMs/ https://github.com/NourozR/Stock-Price-Prediction-LSTM https://www.kaggle.com/pablocastilla/predict-stock-prices-with-lstm/ PEACE! ———————————————————————————————- JOIN NO PMO NATION 👬: ———————————————————————————————- 👬 Instagram: https://www.instagram.com/nopmonation/ ———————————————————————————————- JOIN THE ARMY OF HAPPIER AND STRONGER PEOPLE 👬: ———————————————————————————————- 🎓 SUBSCRIBE ON YOUTUBE: https://goo.gl/JDWLKZ 🎓 JOIN US ON SLACK: https://goo.gl/srBTka 🎓 JOIN MY EXCLUSIVE MAILING LIST: http://eepurl.com/di4dNj ———————————————————————————————- POPULAR EDUCATION SERIES 💝: ———————————————————————————————- 🎓 MASTER NOFAP: https://goo.gl/z6E6HU 🎓 BECOME HAPPIER: https://goo.gl/DZ4cps 🎓 ATTRACT WOMEN: https://goo.gl/MKxdeS 🎓 MACHINE LEARNING: https://goo.gl/hULpKQ 🎓 ARTIFICIAL INTELLIGENCE: https://goo.gl/pzCWpU ———————————————————————————————- HOW TO ASK OSCAR QUESTIONS 🎤: ———————————————————————————————- 👬 MESSAGE ME ON INSTAGRAM: https://www.instagram.com/oscaralsing/ 👬 ASK ME ON SLACK: https://goo.gl/srBTka Linkedin: https://www.linkedin.com/in/oscaralsing/ Facebook: https://www.facebook.com/oscaralsingcom Website: http://www.oscaralsing.com ———————————————————————————————- PRODUCTS I LOVE ❤️: ———————————————————————————————- LIFE-CHANGING BOOKS: https://goo.gl/MMH4XG MY CAMERA/PROGRAMMING GEAR: https://goo.gl/WPCkZr ———————————————————————————————- ABOUT OSCAR 💝: ———————————————————————————————- Oscar is a leader, educator and programmer specialised in Artificial Intelligence and Machine Learning who strives to build a world where all leadership spawns from an intrinsic compassion for others. He is heavily interest in mindfulness and meditation and is a daily Brazilian Jiu-Jitsu practitioner. Furthermore, he Loves lifting heavy things and reads a lot of books and believes in a world where compassion and mutual understanding and respect permeate all of our actions. 🎉 Leader of [More]
Secretly aspire to be a fortune teller to impress your friends? What to build a fun python project? What if you could predict the iPhone price? Yes, even for the latest iPhone 12. #python #project #tutorial You can do this and that too with just 6 simple lines of python code. WHAT IS THE VIDEO ABOUT? • Predict iPhone (especially iPhone 12) price and show off your skills with just 6 lines of Python code Complete Code (give us a star): https://github.com/ProgrammingHero1/predict-iphone-price #python #machine #learning #machinelearning #iphone #iphone12 #apple #pythonhack #funpython #beginners #iphoneprice #iphonefuture Now, if you’re new to the programming world and don’t know what to do, go check out our app and build your own game immediately while learning. Android App: https://bit.ly/AndroidProgHero iPhone Version: https://bit.ly/iOSProgHero CHECK OUT If you hate to study, let’s hear it. Turn your books into audiobooks today: https://bit.ly/FreeAudiobookWithPython ENJOYED THE VIDEO? Save yourself from our Grandma ⁠— she’ll come to your house to steal your old iPhone charger and sell it to Tim Cook if you don’t click on the Like button and also turn the Subscribe button from red to white. If you like and subscribe, she will be ready to make love with you. 😉 OUR SOCIAL MEDIA Watch us on Facebook: https://bit.ly/FBProgHero Peep us on Instagram: https://bit.ly/IGProgHero Fly with us on Twitter: https://bit.ly/TWProgHero Board with us on Pinterest: https://bit.ly/PTProgHero Don’t SHARE this with your friends. They’ll know your secret. We’re always with you. Feel free to mail us anytime you need [More]
The full automated Toolchain from 360° Camera to simulation for digital twin generation The use of a digital twin in the production process will be used, for example, for proactive planning, analysis of existing systems or process-parallel monitoring. Many companies, especially small and medium-sized enterprises, use the technology incorrectly or not. From your point of view, the generation of a digital twin is cost-, time- and resource-intensive. With our approach, these obstacles can be overcome quickly and easily, and the production layout and production logic (e.g. machine types, etc.) can be captured with a 360° Camera. The identification of CAD models and the transfer of geometric and other object data (e.g. machine types) from a reference library significantly reduces the recording of production. With the recognized machines, their properties are also known. With the comparison of the future production program, any simulation of the production can be created. Especially in the planning phase for investments, well-founded results based on a simulation model are indispensable for a target-oriented decision in today’s world. In the presentation we will show you the procedure from scanning, object recognition to simulation and its challenges out of the way.
The Pentagon’s research arm has pumped $1 million into a contract to build an AI tool meant to decode and predict the emotions of allies and enemies. It even wants the AI app to advise generals on major military decisions. DARPA’s backing is the starting pistol for a race with the government and startups to use AI to predict emotions but the science behind it is deeply controversial. Some say it’s entirely unproven, making military applications that much riskier. The previously-unreported work is being carried out under a DARPA project dubbed PRIDE, short for the Prediction and Recognition of Intent, Decision and Emotion. The aim is to create an AI that can understand and predict reactions of a group, rather than an individual, and then offer guidance on what to do next. Think of a military leader who wants to know how a political faction or a whole country would react should he or she take an aggressive action against their leader. In PRIDE, the emotion detection is not for an individual. It’s more as a collective group and even at a national level,” says Dr. Kalyan Gupta, president and founder of Knexus. “To think about, you know, whether a nation state is either angry or agitated.” And it’s no small fry initiative; the plan is for PRIDE to provide recommendations for “international courses of action,” according to a contract description. Whilst DARPA’s project is largely looking at sentiment elicited from text and information posted online, a handful of startups, [More]
🔥Edureka AWS Training: https://www.edureka.co/aws-certification-training This Edureka video on “Deploy an ML Model using Amazon Sagemaker” discusses what is Amazon Sagemaker and how you can build, train and deploy your Machine Learning Models in Amazon Sagemaker. These are the topics covered in the AWS Machine Learning Tutorial video: 00:00:00 Introduction 00:01:14 What is Amazon Sagemaker? 00:04:21 Create your AWS Account 00:06:46 Create your First Notebook Instance 00:17:39 Train your Model on AWS 00:24:37 Deploy your Model on AWS 00:26:33 Evaluate your Model on AWS 00:29:03 AWS SageMaker Case Study: Grammarly 🔹Check Edureka’s complete DevOps playlist here: http://goo.gl/O2vo13 🔹Check Edureka’s Blog playlist here: https://bit.ly/3gfNuZr ——————————————————————————————– 🔴Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ SlideShare: https://www.slideshare.net/EdurekaIN Castbox: https://castbox.fm/networks/505?country=in Meetup: https://www.meetup.com/edureka/ #Edureka #DeployAnMlModelUsingAmazonSagemaker #AWSTutorial #AWSCertification #AWSTraining #AWSMachineLearning #AWSMLDeployment #MachineLearningOnCloud #CloudComputing #AWS ——————————————————————————————– How it Works? 1. This is a 5 Week Instructor led Online Course. 2. Course consists of 30 hours of online classes, 30 hours of assignment, 20 hours of project 3. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 4. You will get Lifetime Access to the recordings in the LMS. 5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! – – – – – – – – – – – – – – About [More]
You are a HUGE football fan. Every week you pick winners in an NFL pick-em’ league. Somehow, all that fan experience doesn’t translate into consistently winning your league. Perhaps you need a more systematic approach that takes some of the emotion out of it. Where to start? Betting spreads provide a consistent and robust mechanism for encapsulating the variables and predicting outcomes of NFL games. In a weekly confidence pool, spreads also perform very well as opposed to intuition-based guessing and “knowledge” from years of being a fan. Can we do better? In this talk, we will discuss an approach to use machine learning algorithms to make improvements on the spread method of ranking winners on a weekly basis as an exercise in winning your friendly neighborhood confidence pool. https://datadialogs.ischool.berkeley.edu/2016/schedule/using-machine-learning-predicting-nfl-games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amit Bhattacharyya Senior Data Scientist Teachers Pay Teachers Amit is the Senior Data Scientist at Teachers Pay Teachers, an online marketplace for teachers to buy, sell and share original educational resources. At TpT, Amit works on developing both technical and modeling infrastructure to analyze customer behavior and ways to more effectively connect buyers and sellers. Amit also teaches in the MIDS program at the UC Berkeley School of Information. He received a Ph.D. in physics from Indiana Universtiy. Previously, he did a two-year stint in advertising, and worked as a quantitative [More]
In this video we will understand how we can implement Diabetes Prediction using Machine Learning. The dataset is taken from Kaggle. Please subscribe and support the channel. github url: https://github.com/krishnaik06/Diabetes-Prediction Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K- You can buy my book on Finance with Machine Learning and Deep Learning from the below url amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1
The aim of the project is about the detection of the emotions elicited by the speaker while talking. As an example, speech produced in a state of fear, anger, or joy becomes loud and fast, with a higher and wider range in pitch, whereas emotions such as sadness or tiredness generate slow and low-pitched speech. Detection of human emotions through voice-pattern and speech-pattern analysis has many applications such as better assisting human-machine interactions. In particular, we are presenting a classification model of emotion elicited by speeches based on deep neural networks (CNNs), SVM, MLP Classification based on acoustic features such as Mel Frequency Cepstral Coefficient (MFCC). The model has been trained to classify eight different emotions (neutral, calm, happy, sad, angry, fearful, disgust, surprise). Our evaluation shows that the proposed approach yields accuracies of 86%, 84%, and 82% using CNN, MLP Classifier and SVM Classifiers, respectively, for 8 emotions using Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset and Toronto Emotional Speech Set (TESS) Dataset. Read more: https://tinyurl.com/y73zmdu3 For more detail visit our website===== Leadingindia.ai Follow us on Twitter ===== https://twitter.com/LeadingindiaAI?s=08 Flow us on instagram===== https://www.instagram.com/technology_ucan/ Like our Facebook page===== https://www.facebook.com/techucan/ Also subscribe this channel for Technical videos===== https://www.youtube.com/channel/UCdimTrr7ZsKbhI50j3VmJiQ Contact us===== madhushi.verma@bennett.edu.in Plz like, comment, share, subscribe and don’t forget to press Bell icon for new updates😊
SingularityDAO ($SDAO) is a project incubated by SingularityNET. The SingularityNET platform utilises artificial intelligence (AI) to manage cryptocurrency portfolios known as Dynasets. Similar to an AI powered decentralized hedge fund, it will make it easier for users to get exposure to the cryptocurrency market and make SMARTER trades. I interview Dr. Ben Goertzel, CEO and Founder of SingularityNET, and AI mastermind. 00:00 Introduction 08:16 Evolution of SingularityNET ($AG)I 09:41 What is SingDAO ($SDAO) and how does DeFi fit in? 12:37 AGI in Bitcoin ($BTC) Futures 13:23 Utility Tokens and Altcoins as alternative to venture capital? 18:40 Baskets of ALT coins – Dynasets 19:21 Collective intelligence for predictions and hedging 20:44 $SDAO launch and tokenomics Learn more about SingularityDAO: https://www.singularitydao.ai Medium: https://medium.com/singularitydao Twitter: https://twitter.com/SingularityDao ●▬▬▬▬▬▬▬Recommendations▬▬▬▬▬▬▬● 📖 Guides, tutorials and insights: https://boxmining.com/ Recommendation List: https://www.cryptoatlas.io/Boxmining 🌼Buy & Sell Bitcoin: https://join.swissborg.com/r/michaeOQZM 🔒Hardware Wallet: http://boxmining.co/ledger 👍🏻Brave Browser: http://boxmining.co/brave 📲FTX Exchange : http://boxmining.co/ftx 📲Binance Exchange : http://boxmining.co/binance ●▬▬▬▬▬▬▬▬▬▬Community▬▬▬▬▬▬▬▬▬● Boxmining clips: https://www.youtube.com/channel/UCjFy3VBgOZanySOLhQu6GaQ Boxmining News Website: https://www.boxmining.com/ Telegram Announcements: https://t.me/boxminingChannel ●▬▬▬▬▬▬▬▬▬▬▬Social▬▬▬▬▬▬▬▬▬▬▬● Twitter: https://twitter.com/boxmining Discord: https://discord.gg/9qCpqpZm8G Facebook: https://www.facebook.com/boxmining ●▬▬▬▬▬▬▬▬▬▬Disclaimer▬▬▬▬▬▬▬▬● I’m not a professional financial adviser and you should always do your own research. I may hold the cryptocurrencies talked about in the video.
As part of Samsung NEXT’s “How AI is changing the world” series, Martin Aguinis, Product Marketing Manager at Google, describes how the search giant is using AI in its applications, as well as how it is making machine learning applications more widely available to other companies.
This is a series where I walk through the engineering steps and challenges on how to build an Artificial intelligence voice assistant, similar to google home or Amazon Alexa, with Python and PyTorch on a Raspberry Pi. I leverage the latest machine and deep learning techniques to achieve this. In this video, I show how you can build a wake word detector (keyword spotting) using recurrent neural networks specifically LSTMs. Audo Studio | Automagically Make Audio Recordings Studio Quality https://www.audostudio.com/ Magic Mic | Join waitlist and get it FREE forever when launched! 🎙️ https://magicmic.ai/ Audo AI | Audio Background Noise Removal Developer API and SDK https://audo.ai/ Discord Server: Join a community of A.I. Hackers https://discord.gg/9wSTT4F Subscribe to my email newsletter for updated Content. No spam 🙅‍♂️ only gold 🥇. https://bit.ly/320hUdx Github: https://github.com/LearnedVector/A-Hackers-AI-Voice-Assistant Parts: raspberry pi 4 model b – https://www.amazon.com/gp/product/B07TC2BK1X/ref=ppx_yo_dt_b_search_asin_title?ie=UTF8&psc=1 ReSpeaker 2 mic array hat – https://www.amazon.com/gp/product/B07D5X7N6W/ref=ppx_yo_dt_b_search_asin_title?ie=UTF8&psc=1 portable mini speaker – https://www.amazon.com/gp/product/B07RJR1XPH/ref=ppx_yo_dt_b_search_asin_title?ie=UTF8&psc=1 micro sd – https://www.amazon.com/gp/product/B07KY36H93/ref=ppx_yo_dt_b_search_asin_title?ie=UTF8&psc=1
Build A Virtual Assistant Using Python ⭐Please Subscribe !⭐ ⭐Support the channel and/or get the code by becoming a supporter on Patreon: https://www.patreon.com/computerscience ⭐Websites: ► http://everythingcomputerscience.com/ ⭐Helpful Programming Books ► Python (Hands-Machine-Learning-Scikit-Learn-TensorFlow): https://amzn.to/2AD1axD ► Learning Python: https://amzn.to/3dQGrEB ►Head First Python: https://amzn.to/3fUxDiO ► C-Programming : https://amzn.to/2X0N6Wa ► Head First Java: https://amzn.to/2LxMlhT #VirtualAssistant #Python
How can artificial intelligence (AI) improve beer? Rob McInerney, the founder & CEO of Intelligent Layer and co-founder of IntelligentX Brewing Company, explains the use of AI in improving everyday products. Learn more about Rob McInerney at http://www.tedxgoodenoughcollege.com/portfolio/rob-mcinerney-using-artificial-intelligence-to-make-everyday-products-better/ Dr Rob McInerney is the founder & CEO of Intelligent Layer and co-founder of IntelligentX Brewing Company. He completed his PhD in Machine Learning at the University of Oxford, where his research focused on how intelligent machines should learn from experience through a process of reinforcement learning. In 2015, Rob founded Intelligent Layer to re-envisage the relationship between human beings and intelligent technology, underpinned by his belief that AI can help us navigate a world that is changing faster. Last year, he created IntelligentX Brewing Company, a self-evolving beer brand that uses AI to optimise beer recipes using customer feedback, which Popular Science voted “the third greatest software innovation of 2016”. Intelligent Layer recently graduated from Techstars in New York City, one of the world’s top accelerator programmes. Rob regularly contributes to topics around AI and machine learning and has been featured in Time, Wired, Forbes, The Guardian & The Huffington Post This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
Text summarization is the process of creating a short, accurate, and fluent summary of a longer text document. It is the process of distilling the most important information from a source text. Automatic text summarization is a common problem in machine learning and natural language processing (NLP). Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover relevant information and to consume relevant information faster. 🔊 Watch till last for a detailed description 01:21 What is text summarization? 05:19 Installing the packages 15:10 Sentence tokenization 👇👇👇👇👇👇👇👇👇👇👇👇👇👇 ✍️🏆🏅🎁🎊🎉✌️👌⭐⭐⭐⭐⭐ ENROLL in My Highest Rated Udemy Courses to 🔑 Unlock Data Science Interviews 🔎 and Tests 📚 📗 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: https://bit.ly/bert_nlp 📊 📈 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: https://bit.ly/udemy95off_kgptalkie 📘 📙 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: https://bit.ly/intro_nlp . 📈 📘 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: https://bit.ly/regression-python 📙📊 2021 R 4.0 Programming [More]
Can an algorithm help you improve your penalty kick or tennis serve? In this episode of Making with Machine Learning, Dale Markowitz chats with Machine Learning Engineer Zack Akil to learn about how Google Cloud’s ML services, like Cloud AutoML vision and the Video Intelligence API, can be used to analyze, assess, and improve your game. 0:00 – Introduction 0:40 – Overview 2:05 – What was measured? 3:37 – What powered the demo? 4:12 – Problems/Challenges 4:45 – Training Auto ML Vision model 5:50 – Using it for tennis serve Blog Post → https://goo.gle/3etkKdM Code → https://goo.gle/3h4hIOZ Watch more episodes of Making with Machine Learning → https://goo.gle/2YysJRY Subscribe to get all the episodes as they come out → https://goo.gle/GCP Follow @dale_on_ai on Instagram → https://goo.gle/2Oo9lkP #MakingWithMachineLearning #MakingWithML Product: Video Intelligence API, Cloud AutoML Vision; fullname: Dale Markowitz;
🔥Edureka and NIT Warangal Post Graduate Program on AI and Machine Learning: https://www.edureka.co/post-graduate/machine-learning-and-ai This Edureka Session explores and analyses the spread and impact of the novel coronavirus pandemic which has taken the world by storm with its rapid growth. In this session, we shall develop a machine learning model in Python to analyze what has been its impact so far and analyze the outbreak of COVID 19 across various regions, visualize them using charts and tables, and predict the number of upcoming confirmed cases. Finally, we’ll conclude with a few safety measures that you can take to save yourself and your loved ones from getting adversely affected in the hour of crisis. 02: 53 Introduction to COVID 19  05:49 Case Study: the outbreak of COVID 19 57:20 Conclusion 🔸Datasets and code: https://bit.ly/3tFxZQa 🔸Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm ——————————–Edureka Training and Certifications ——————————– 🔵 Machine Learning Course using Python: http://bit.ly/37CWMcy 🟣 Machine Learning Engineer Masters Program: http://bit.ly/320TkHy 🔵 Deep Learning using TensorFlow: http://bit.ly/2P0M1dv 🟣 PG in Artificial Intelligence and Machine Learning with NIT Warangal: https://www.edureka.co/post-graduate/machine-learning-and-ai 🔵 Post Graduate Certification in Data Science with IIT Guwahati: https://www.edureka.co/post-graduate/data-science-program (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV ——————————————————————————————– Edureka Community: https://bit.ly/EdurekaCommunity Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates Slideshare: https://www.slideshare.net/EdurekaIN/ Meetup: https://www.meetup.com/edureka/ #edureka #MLedureka #covidPrediction #FutureOfAIML #covid19outbreak #covid19cases #machineLearningusingPython ——————————————————————————————– How it Works? 1. This is a 5 Week Instructor led Online Course,40 [More]
► A digital artist is teaching machines how to interpret paintings as real life people and results are amazing. Nathan Shipley is a San Francisco based artist who uses latest digital technology and in particular Artificial Intelligence to create some pretty cool artistic stuff. In 2018 he used Deepfake technology to bring to life Salvador Dali for the Dali Museum in Florida, who was able to talk and interact with visitors. In his latest project, using machine learning and generative art, he is exploring how artificial intelligence recreates historical figures from paintings. Please check video where some of his work is presented. And a warning again, please don’t freak out, I’ve added some subtle animation to give them additional layer of realism. Enjoy. Please follow Nathan’s work here: https://www.instagram.com/nathan_shipley_vfx/ https://twitter.com/CitizenPlain http://www.nathanshipley.com/ Featured in this video: King Henry VII, King Henry VIII, Anne Boleyn, King Edward VI, Queen Mary I (Mary Tudor), Elizabeth I (young, middle and old age), Mona Lisa and Rembrandt. ——— If you have enjoyed the video, please show some love by LIKING, COMMENTING and SUBSCRIBING to my channel! – – – – – – – – – – – – – – – – – – – – #MysteryScoop #HistoricalPaintings #HistoricalPortraits #AIStuff #ColorizedPhotos #DigitalAnimation #ArtificialIntelligence – – – – – – – – – – – – – – – – – – – – For any Copyright issues, please reach out to us first before filing a claim with YouTube. Send us a message or email [More]
Build A Smart AI Chat Bot Using Python & Machine Learning ⭐Please Subscribe !⭐ ⭐Support the channel and/or get the code by becoming a supporter on Patreon: https://www.patreon.com/computerscience ⭐Website: http://everythingcomputerscience.com/ ⭐Helpful Programming Books ► Python (Hands-Machine-Learning-Scikit-Learn-TensorFlow): https://amzn.to/2AD1axD ► Learning Python: https://amzn.to/3dQGrEB ►Head First Python: https://amzn.to/3fUxDiO ► C-Programming : https://amzn.to/2X0N6Wa ► Head First Java: https://amzn.to/2LxMlhT Promising new research on kidneys: https://wonderfulengineering.com/this-artificial-kidney-eliminates-the-need-for-kidney-dialysis/?fbclid=IwAR19Olftqa9vr0HEhwl51c89OPN6RGsxPNDDJB2rzhqdKkIVGYYXeGCF1Ds Mayo Clinic Website on Chronic Kidney Disease: https://www.mayoclinic.org/diseases-conditions/chronic-kidney-disease/symptoms-causes/syc-20354521
WRT-1025: Using AI/ML Design Patterns for Digital Twins and Model-Centric Engineering – Dr. Mark Austin, University of Maryland Presented on November 18, 2020 at the 12th Annual SERC Sponsor Research Review. Through various keynotes and breakout sessions, the SSRR focuses on the latest research results from SERC researchers aligned with the emerging and critical research needs of sponsors. EVENT PAGE: https://sercuarc.org/research-reviews/2020-serc-research-review
Stock Predictions Using Machine Learning Algorithms #Python #Stocks #MachineLearning Disclaimer: The material in this video is purely for educational purposes and should not be taken as professional investment advice. Invest at your own discretion. ⭐Please Subscribe !⭐ ▶️ Get 4 FREE stocks (valued up to $1600) on WeBull when you use the link below and deposit $100: https://act.webull.com/kol-us/share.html?hl=en&inviteCode=LR6VIpFiAkPe ▶️ Earn $10 in Bitcoin by signing up with BlockFi and depositing $100 or more: https://blockfi.com/?ref=e5b523e0 ⭐Website: http://everythingcomputerscience.com/ ⭐Support the channel on Patreon: ► https://www.patreon.com/computerscience ⭐Helpful Programming Books ► Python (Hands-Machine-Learning-Scikit-Learn-TensorFlow): https://amzn.to/2AD1axD ► Learning Python: https://amzn.to/3dQGrEB ►Head First Python: https://amzn.to/3fUxDiO ► C-Programming : https://amzn.to/2X0N6Wa ► Head First Java: https://amzn.to/2LxMlhT
Hi. In this lecture will transform tokens into features. And the best way to do that is Bag of Words. Let’s count occurrences of a particular token in our text. The motivation is the following. We’re actually looking for marker words like excellent or disappointed, and we want to detect those words, and make decisions based on absence or presence of that particular word, and how it might work. Let’s take an example of three reviews like a good movie, not a good movie, did not like. Let’s take all the possible words or tokens that we have in our documents. And for each such token, let’s introduce a new feature or column that will correspond to that particular word. So, that is a pretty huge metrics of numbers, and how we translate our text into a vector in that metrics or row in that metrics. So, let’s take for example good movie review. We have the word good, which is present in our text. So we put one in the column that corresponds to that word, then comes word movie, and we put one in the second column just to show that that word is actually seen in our text. We don’t have any other words, so all the rest are zeroes. And that is a really long vector which is sparse in a sense that it has a lot of zeroes. And for not a good movie, it will have four ones, and all the rest of zeroes [More]
WRT-1025: Using AI/ML Design Patterns for Digital Twins and Model-Centric Engineering – Dr. Mark Austin, University of Maryland Presented on November 18, 2020 at the 12th Annual SERC Sponsor Research Review. Through various keynotes and breakout sessions, the SSRR focuses on the latest research results from SERC researchers aligned with the emerging and critical research needs of sponsors. EVENT PAGE: https://sercuarc.org/research-reviews/2020-serc-research-review
PyPower Projects – Experience The Power Of Python Whatsapp Group Link : https://rebrand.ly/PyPower_Group GitHub Repository Link : https://github.com/pypower-codes/Emotion-Detection.git Subscribe Channel : https://rebrand.ly/PyPower-Projects PyPower is an initiative with the vision to integrate every TechGeek to an integrated platform in order to devour the essence of Python. We will be coming up with various extraordinary real-life projects as well as awesome technical programs easily implemented through Python. Will present a video related to this every week along with its explanation, working, programming screencast and code. Open the essence of images by OpenCV. Embed numeric operations in Python using NumPy. Come in flow of machine learning with TensorFlow. Dive deep into ocean of deep learning with Keras. Plot anything anytime anywhere using Matplotlib. Automate your browser using Selenium. Let your Shell strengthen to its Apex and be the Impulse of your work. Stay Tuned. Follow us on Instagram: http://www.instagram.com/py_power Follow us on Facebook: https://www.facebook.com/py.power.7 View us on GitHub: /pypower-codes YouTube : https://rebrand.ly/PyPower-Projects Whatsapp Group Link : https://rebrand.ly/PyPower_Group Do Like, Share and Subscribe for regular updates… #Python #PyPower #AI #Tensorflow