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The “Laws of Attraction” are real; inasmuch, there is a Divine Component. Connecting Personality Type to The Laws of Attraction positions you for immediate manifestation of your desires while unleashing your preordained purpose. Your Creator gave you a unique Personality Type for a reason. There are many words that describe Dr. D Ivan Young, but here are the few that I chose – discerning, enlightened, a spiritual teacher and sagacious philosopher. Seldom does someone possess the ability to connect, at a core level, to impact so many different and varying people. His witty insight into how, and moreover why, people do the things they do is astonishing. Having known Dr. Young for a few years, never have I seen him at a loss for words or searching for an answer. His compassion, his love, and his authentic way of communicating to us exactly what we need to hear and when we need to hear it has profoundly changed my life, and the lives of everyone I’ve witnessed him come in contact with. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Presentation on Facial Emotion Recognition System Using Machine Learning!! (Created By) Manisha Singh Himanshu Tuli Nidhi Singh
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In this video, we are building a Fake News Prediction System using Machine Learning with Python. We will be using Logistic Regression model for prediction. Enroll at One Neuron to learn from 100 courses in one subscription with 5% discount: https://courses.ineuron.ai/neurons/Tech-Neuron?campaign=affiliate&coupon_code=SID5 Hi guys! I am Siddhardhan. I work in the field of Data Science and Machine Learning. It all started with my curiosity to learn about Artificial Intelligence and the ability of AI to solve several Real Life Problems. I worked on several Machine Learning & Deep Learning projects involving Computer Vision. I am on this journey to empower as many students & working professionals as possible with the knowledge of Machine Learning and Artificial Intelligence. Hello everyone! I am setting up a donation campaign for my YouTube Channel. If you like my videos and wish to support me financially, you can donate through the following means: From India 👉 UPI ID : siddhardhselvam2317@oksbi Outside of India? 👉 Paypal id: siddhardhselvam2317@gmail.com (No donation is small. Every penny counts) Thanks in advance! Let’s build a Community of Machine Learning experts! Kindly Subscribe here👉 https://tinyurl.com/md0gjbis I am making a “Hands-on Machine Learning Course with Python” in YouTube. I’ll be posting 3 videos per week. 2 videos on Machine Learning basics (Monday & Wednesday Evening). 1 video on a Machine Learning project (Friday Evening). Dataset file: https://www.kaggle.com/c/fake-news/data?select=train.csv Colab file: https://colab.research.google.com/drive/1xief9dGx_qsgr39Rx0BlxRFXmtOrnCU7?usp=sharing Download the Course Curriculum File from here: https://drive.google.com/file/d/17i0c6SmncNuwSgr9W1MRRk3YYdEOP9Gd/view?usp=sharing LinkedIn: https://www.linkedin.com/in/siddhardhan-s-741652207 Telegram Group: https://t.me/siddhardhan Facebook group: https://www.facebook.com/groups/490857825649006/?ref=share #machinelearning #machinelearningproject #machinelearningtutorial #machinelearningtraining #machinelearningcourse #python #pythonproject [More]
This KNN Algorithm in Machine Learning tutorial will help you understand what is KNN, why do we need KNN, and how KNN algorithm works. You will learn how do we choose the factor ‘K’, when do we use KNN, and you will also see a use case demo to predict whether a person will have diabetes or not using the KNN algorithm. Below topics are explained in this K-Nearest Neighbor Algorithm (KNN Algorithm) tutorial: 00:00 – 00:57 Introduction to KNN(K Nearest Neighbor) 00:57 – 02:33 Why do we need KNN? 02:33 – 03:51 What is KNN? 03:51 – 05:46 How do we choose the factor ‘K’? 05:46 – 06:42 When do we use KNN? 06:42 – 09:19 How does the KNN algorithm work? 09:19 – 27:42 Use case – Predict whether a person will have diabetes or not 🔥 Enroll for FREE Machine Learning Course & Get your Completion Certificate: https://www.simplilearn.com/learn-machine-learning-basics-skillup?utm_campaign=KNNInMLMachineLearning&utm_medium=Description&utm_source=youtube Dataset Link – https://drive.google.com/drive/folders/1YylTjWxmkUVdurMSDjl84dstCKZL6wH8 ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4 You can also go through the slides here: https://goo.gl/XP6xcp #KNNAlgorithmInMachineLearning #KNNAlgorithm #KNN #KNearestNeighbor #KNNMachineLearning #KNNAlgorithmPython #KNearestNegighborMachineLearning #MachineLearningAlgorithm #MachineLearning #Simplilearn What is KNN? K-Nearest Neighbors is one of the simplest supervised machine learning algorithms used for classification. It classifies a data point based on its neighbors’ classifications. It stores all available cases and classifies new cases based on similar features. When Do We Use the KNN Algorithm? The KNN algorithm is used in the following [More]
Upscale/Enhance your VIDEOS using Artificial Intelligence! (HD to 4K) ►Download Topaz Video Enhance AI- https://www.topazlabs.com/video-enhance-ai/ref/1223/?campaign=YouTube%20video In this music video/filmmaking/vlog/anime editing/amv/sony vegas/after effects tutorial, I will show you how to upscale/ deinterlace/ denoise/ deflicker/ deblock/ enhance/ restore your old/low quality/interlaced video upto 8k resolution with the power of A.I.-Artificial Intelligence! After hours of research,trial,testing and comparing the different tools/software/techniques available in the market,I’ve come to the conclusion that Topaz Video Enhance AI is the best upscaling tool. _ ⚡️R E S O U R C E S ►The Anatomy of AMV Flow- http://bit.ly/2q5QDG1 ►How to convert raw anime- https://youtu.be/ckgrfrXqY8U ►Twixtor Time-Remapping 101- http://bit.ly/Twixtor2019 ►Complete AMV Guide (2 hours)- https://youtu.be/H2MWVNLjNWA _ ★Check out my official presets↓ ►Download Vegas Ultra Transitions & FX Pack(Best-Seller) – http://bit.ly/UltraV3 ►Download Pro’s All-In-One Preset Bundle (2000+Presets)- https://goo.gl/zJ66oW _ The software I use👇 ►Download Vegas Pro – https://bit.ly/Vegas–Pro ►Download After Effects- https://bit.ly/After–Effects _ ► STAY CONNECTED ►Discord- Shubh# 3265 ►Download Presets- https://www.pro-edits.com/ ►Business inquires- realshubhjain@gmail.com _ Outro Music – Neffex – Best of me _ (Tags) sony vegas,vegas pro,sony vegas tutorial,vegas pro tutorial,sony vegas transition tutorial,vegas pro transition tutorial,pro edits,how to,sony vegas effects,transitions and effects,sony vegas editing tutorial,filmmaking,preset pack,free preset pack,smooth transitions,amv,music video,music video effects,music video tutorial,how to make an amv,amv sony vegas,anime,vegas preset pack,twixtor,amv tutorial,upscale old videos,enahnce video quality,restore old footage,deinterlace video,deflicker video, remove flickers from video, upscale anime, upscale tutorial amv, vegas pro upscale tutorial,video enhance ai, upsacle videos using ai,artificial intelligence _ Upscale/Enhance your VIDEOS using Artificial Intelligence! (HD to 4K)
Get a Free Pair of Wireless Bluetooth Headphones at Micro Center: https://micro.center/9a49a2 Check out the Micro Center Custom PC Builder: https://micro.center/9dec49 Instagram http://instagram.com/jlaservideo Here’s how I made a real Harry Potter inspired invisibility cloak/shield using a digital passthrough system with AI software combined with lenticular lenses. The camera mounted on the back side of the screen sends images through an AI which generates a 3d view of the 2d input image. Then the front camera tracks the viewers location and projects alters the 3d image to display the correct prospective on the screen for that viewer. Lenticular lenses are also used to blend the digital image with the background as well as attempt to project a 3d stereoscopic view to the viewer (However this implementation still needs some work) Dr. Octopus Video: https://youtu.be/_ECHJsBeOzI Augmented Startups: https://www.youtube.com/channel/UCFJPdVHPZOYhSyxmX_C_Pew AI 2D to 3D: https://shihmengli.github.io/3D-Photo-Inpainting/ Facebook: http://goo.gl/ZzRoKM Playlist of Every Video: http://goo.gl/QVU2Wz If you liked this video, check out more on my channel http://youtube.com/jlaservideo Music: https://goo.gl/7bB4Jk
🔵 Intellipaat natural language processing in python course: https://intellipaat.com/nlp-training-course-using-python/ In this natural language processing video, you will learn what is a natural language, text mining in NLP, file handling in python, NLTK package, tokenization, artificial intelligence, hands-on demo, frequency distribution, stop words, and the concepts of bigrams, trigrams, and n-grams, NLP interview questions in detail. This NLP with Deep Learning and Machine Learning video is a must-watch for everyone who wants to learn NLP and make a career in the AI domain. #NaturalLanguageProcessing #NLPdeeplearning #NLPMachineLearning #NLPPython #NLPCourse #NLPTraining #NLPTutorial #Intellipaat The following topics are covered in this video: 01:47 – Introduction to NLP 03:41 – Tokenization 12:13 – Lemmatization 13:36 – Parts of Speech Tagging 16:12 – Named Entity Recognition 18:29 – Introduction to Spacy 26:07 – Sentiment Analysis using NLTK 46:26 – Text Mining 47:12 – Need of Text Mining 48:19 – Natural Language Processing(NLP) 49:21 – Installing Anaconda 51:19 – OS Module in Python 58:35 – File Handling in Python 59:26 – Creating File Object 01:00:35 – Reading from a File 01:04:02 – Writing to a File 01:08:07 – Working with Word Files 01:13:27 – Natural Language Toolkit (NLTK) 01:14:12 – NLTK Corpora 01:15:51 – Chunking 01:36:34 – Chinking 01:43:04 – Why Artificial Intelligence? 01:50:35 – Machine Learning 01:55:50 – Machine Learning Types 02:05:12 – Introduction to Deep Learning 02:07:40 – Application of Deep Learning 02:10:07 – What is Neural Network? 02:17:10 – Activation Functions 02:21:23 – Perceptron Training Algorithm 02:24:11 – What are Tensors? 02:26:07 – Program [More]
PM KISAN eKYC through CSC Biometric | Pm kisan ekyc Without OTP Using Fingerprint full process This video is about PM Kisan ekyc Using Startech Finger Print Scanner through CSC portal To get further benefits under PM Kisan Samman Nidhi Yojana, all of you farmers will have to get KYC done. The link was also added on the official website but due to technical problem there, the gender has been removed. A tweet was made by CSC yesterday in which it has been told that now Delhi can do KYC of farmers through CSC portal. In this video I have streamed a complete video to all of you about this process, how you have to do KYC of farmers. dinesh tyagi (CEO ) Dear VLE The eKYC for PM KISAN is enabled through CSCs . Currently you will be able to work only using Startek Biometric device and soon others will also be enabled. Use digital Seva portal to login or click on csc login button at https://Pmkisan.gov.in.Kindly help every farmer Important Link Topics covered this video pm kisan ekyc kaise kare, pm kisan ekyc, pm kisan ekyc through csc, pm kisan ekyc without otp, csc pm kisan ekyc, pm kisan ekyc new update, pm kisan ekyc data not found problem, pm kisan gov in ekyc, ekyc pm kisan online, aadhar ekyc pm kisan without otp, pm kisan aadhar ekyc kaise kare, pm kisan kyc online,kisan card ekyc, pm kisan,ekyc pm kisan yojana, pm kisan ekyc problem, pm kisan kyc [More]
Julia Computing delivers JuliaSim as an answer to accelerating simulations through digital-twin (or surrogate) modeling. By blending classical, physical modeling with advanced scientific machine learning (SciML) techniques, JuliaSim provides a next-generation platform for building, accelerating, and analyzing models. https://juliacomputing.com/products/juliasim/ https://arxiv.org/abs/2105.05946 https://sciml.ai/ 00:00 Julia Computing introduction 00:46 How JuliaSim solves industrial modeling challenges 03:59 Real-world success with JuliaSim 04:51 Example model 05:37 Launching JuliaSim’s FMU Accelerator 06:29 Surrogatizing the example model 08:46 Analyzing the surrogate model via diagnostic dashboard 15:25 Workflow integration review 15:53 JuliaSim as a fully-featured simulation platform 16:09 Cost versus Benefit For more information, contact info@juliacomputing.com #sciml #machinelearning #ai #modeling #simulation
Iran is set to be the first country to roll out a food rationing scheme based on new biometric IDs. Where vaccine passports failed, food passports will now be eagerly accepted by hungry people who can’t afford rapidly inflating food prices. This is the realization of a longstanding agenda by the Rockefeller/UN/WEF crowd to, as Kissinger put it, “control food, and control people.” Christian breaks it down in this Ice Age Farmer broadcast. FULL SHOW NOTES: https://www.iceagefarmer.com/2022/05/17/iran-digital-food-rationing-rolls-out-using-biometric-ids-amid-food-riots/ on TELEGRAM: https://t.me/iceagefarmer on bitchute: https://bitchute.com/iceagefarmer on Odysee: https://odysee.com/@iceagefarmer THANK YOU FOR YOUR SUPPORT: https://patreon.com/iceagefarmer https://paypal.me/iceagefarmer – other methods: https://iceagefarmer.com/support Ice Age Farmer Guilded (chat) group: http://iceagefarmer.com/guilded The Victory Seed — easy pamphlet to share: http://thevictoryseed.org __ ⇒ IAF Wiki – read history, understand cycles, know what’s coming: http://wiki.iceagefarmer.com/wiki/History ⇒ Maps from previous cycles: http://wiki.iceagefarmer.com/wiki/Strategic_Relocation:_Maps ⇒ Join the email list – stay connected: http://iceagefarmer.com/mail *** SUPPORTERS – I recommend (because I use personally) *** STORED FOOD (+ more) @ MyPatriotSupply: https://iceagefarmer.com/prep FREEZE DRY YOUR OWN FOOD (like printing money, but food): https://iceagefarmer.com/harvestright BUY SEEDS @ TRUE LEAF MARKET: https://iceagefarmer.com/trueleaf EMP-proof Solar: mention IAF save $250 https://Sol-ark.com BEST CBD: https://bignuggetfarm.com 10% code: IAF2018 ⇒ More books: http://amazon.com/shop/iceagefarmer ⇒ Stored food: http://iceagefarmer.com/prep ___ LINKS:
Venture Café 134 | September 9, 2021 Using Artificial Intelligence to Make a Digital Twin Speakers: Miguel Dickson https://venturecafephiladelphia.org/speakers/miguel-dickson/ RoadBotics Head of Data and AI Miguel Dickson will discuss how computer vision artificial intelligence techniques work, how RoadBotics uses this technology for assessing roads and for automatically tagging assets in a digital twin. —- For more programs and events, visit http://www.sciencecenter.org. Keep up with Science Center news, events, and more by subscribing to our emails at http://eepurl.com/ha_u1D
Natural Language Processing is a technique that is widely used in the field of AI and Machine Learning. In this video, you learn about the NLTK library and its use for natural language processing and text mining tasks. You will look at Speech Recognition, Spam Filtering, and Sentiment Analysis. You will understand text extraction and NLP workflow. Using the NLTK Python library, you will perform a hands-on demo on processing brown corpus and structuring sentences. 🔥Free AI Course: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=NLTKPythonTutorial&utm_medium=Description&utm_source=youtube ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Artificial Intelligence training videos: https://bit.ly/2Li4Rur #ArtificialIntelligence #AI #MachineLearning #SimplilearnAI #RiseofAI #FutureOfAI #SimplilearnTraining #DeepLearning #Simplilearn Simplilearn’s Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems without explicit programming. Why learn Artificial Intelligence? The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills. You can gain in-depth knowledge of Artificial Intelligence by taking our Artificial Intelligence certification training course. Those who [More]
Stock Price Prediction Using Python & Machine Learning (LSTM). In this video you will learn how to create an artificial neural network called Long Short Term Memory to predict the future price of stock. Disclaimer: The material in this video is purely educational and should not be taken as professional investment advice. Invest at your own discretion. NOTE: In the video to calculate the RMSE I put the following statement: rmse=np.sqrt(np.mean((predictions- y_test)**2)) When in fact I meant to put : rmse=np.sqrt(np.mean(((predictions- y_test)**2))) You can use the following statements to calculate RMSE: 1. rmse =np.sqrt(np.mean(((predictions- y_test)**2))) 2. rmse = np.sqrt(np.mean(np.power((np.array(y_test)-np.array(predictions)),2))) 3. rmse = np.sqrt(((predictions – y_test) ** 2).mean()) Please Subscribe ! ⭐Get the code here⭐: https://www.patreon.com/computerscience ▶️ Get 4 FREE stocks (valued up to $1600) on WeBull when you use the link below and deposit $100 or more: 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 ⭐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 ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 📚Helpful Financial Books📚 ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🌟Stock Market Investing Books: ✔️The Bogleheads’ Guide to Investing https://amzn.to/3s0icxA ✔️The Intelligent Investor https://amzn.to/34Mj7t1 ✔️A Random Walk Down Wall Street https://amzn.to/3Bv0ghW 🌟Money Mindset Books ✔️Rich Dad Poor Dad: https://amzn.to/3rZW6eE ✔️Get Good With Money: Ten Simple Steps To Becoming Financially Whole: https://amzn.to/3I1UXc1 #StockPrediction #Python #MachineLearning
Hello Friends, In this episode we are going to do Emotion Detection using Convolutional Neural Network(CNN). I will do the step by step implementation starting for the dataset download, accessing data set, preprocessing images, designing CNN, training CNN , saving trained model and using that saved model to do the emotion detection on video or live stream. Code link : https://github.com/datamagic2020/Emotion_detection_with_CNN Emotion detection in 5 Lines using pre-trained model -: https://youtu.be/ERXqo_ZEnIo =========== Time Code =========== 00:01 Introduction to Emotion Detection using CNN 01:21 FER 2013 Facial Expression Dataset 04:12 files in emotion detection project 05:52 Image preprocessing using Image Data Generator 08:09 Design/Create Convolution Neural Network for Emotion Detection 10:33 Train out CNN with FER 2013 Dataset / Train CNN for Emotion Detection 11:59 Save the trained model weights and structure 13:08 Test Trained Emotion Detection model 14:15 Load saved model 15:05 Access Video or Camera Feed for testing Emotion Detection model 16:20 Face detection with Haarcascade classifier 18:16 Detect and Highlight each face on video 20:06 Predict Emotion using model 20:21 Display Emotion on video 21:53 Emotion Detection Demo 24:58 emotion detection improvisations Stay tuned and enjoy Machine Learning !!! Cheers !!! #emotiondetection #CNN #DeepLearning Connect with me, ☑️ YouTube : https://www.youtube.com/c/DataMagic2020 ☑️ Facebook : https://www.facebook.com/datamagic2020 ☑️ Instagram : http://instagram.com/datamagic2020 ☑️ Twitter : http://www.twitter.com/datamagic5 ☑️ Telegram: https://t.me/datamagic2020 For Business Inquiries : datamagic2020@gmail.com Best book for Machine Learning : https://amzn.to/3qCe0Rf 🎥 Playlists : ☑️Machine Learning Basics https://www.youtube.com/playlist?list=PLTmQbi1PYZ_E1iTkBrZWK_htO0hY4vcGK ☑️Feature Engineering/ Data Preprocessing https://www.youtube.com/playlist?list=PLTmQbi1PYZ_EnBmO1-E0Z81ArnE-zSR1a ☑️OpenCV Tutorial [Computer Vision] https://www.youtube.com/playlist?list=PLTmQbi1PYZ_GrjMHiGCYa0WyDZfxu-yTz ☑️Machine Learning Algorithms [More]
#emotiondetection #opencv #cnn #python Code – https://github.com/akmadan/Emotion_Detection_CNN Telegram Channel- https://t.me/akshitmadan Instagram- https://www.instagram.com/akshitmadan_/?hl=en LinkedIn- https://www.linkedin.com/in/akshit-madan-394a82a6 Books for Reference – Python for Beginners – https://amzn.to/3oZmqSm Complete Data Science – https://amzn.to/3nTZkuV Data Science Handbook – https://amzn.to/3oYHHvt Book for Computer Vision – Learning OpenCV by O’Reilly – https://amzn.to/391GJJo
Join me live as we walk through a step by step (hands-on lab) process of building chat bots using Power Virtual Agents in Microsoft Teams. The chat bot will provide the user status information of their Help Desk ticket. We will be calling Power Automate flows from Power Virtual Agents chat bots to check the ticket status. We will be leveraging Power Virtual Agents with Microsoft Dataverse for Teams. I will answer your questions live during the session. Microsoft Dataverse for Teams delivers a built-in low code data platform for Microsoft Teams, and provides relational data storage, rich data types, enterprise grade governance, and one-click solution deployment. In this live session, we will learn how to build chat bots, call flow from chat bot to query Dataverse Tables, return rich text from flow to bot & more. 📢 Q&A Rules: 👉 I will open the floor for live Q/A at end of session. 👉 Put “Q:” in front of your comments and post your question. 👉 Please do not re-post your questions. 👉 I will try to answer as many questions as possible. 👉 If you SPAM your question/comments, you will be put in timeout. #PowerVirtualAgents #MicrosoftTeams #Dataverse #Live #RezaDorrani
Companies are using “fake” AI-generated faces in ads. They can be used as stock images or to replace real people in what may be an uncomfortable ad to appear in. But there are potential pitfalls, according to tech columnist Ramona Pringle. »»» Subscribe to CBC News to watch more videos: http://bit.ly/1RreYWS Connect with CBC News Online: For breaking news, video, audio and in-depth coverage: http://bit.ly/1Z0m6iX Find CBC News on Facebook: http://bit.ly/1WjG36m Follow CBC News on Twitter: http://bit.ly/1sA5P9H For breaking news on Twitter: http://bit.ly/1WjDyks Follow CBC News on Instagram: http://bit.ly/1Z0iE7O Download the CBC News app for iOS: http://apple.co/25mpsUz Download the CBC News app for Android: http://bit.ly/1XxuozZ »»»»»»»»»»»»»»»»»» For more than 75 years, CBC News has been the source Canadians turn to, to keep them informed about their communities, their country and their world. Through regional and national programming on multiple platforms, including CBC Television, CBC News Network, CBC Radio, CBCNews.ca, mobile and on-demand, CBC News and its internationally recognized team of award-winning journalists deliver the breaking stories, the issues, the analyses and the personalities that matter to Canadians.
Many techniques have been proposed to both accelerate and compress trained Deep Neural Networks (DNNs) for deployment on resource-constrained edge devices. Software-oriented approaches such as pruning and quantization have become commonplace, and several optimized hardware designs have been proposed to improve inference performance. An emerging question for developers is: how can we combine and automate these optimizations together? In this session, we examine a real-world use-case where DNN design space exploration was used with the optimized Ethos-U55 NPU to leverage SW and HW optimizations in one workflow. We will show how to automatically produce optimized TensorFlow Lite CNN model architectures, and speed up the dev-to-deployment process. We’ll present insights from testing Arm’s Vela compiler, FVP and configurable NPU to boost throughput 1.7x and reduce cycle count by 60% for image recognition tasks, enabling complex models typically not available for inference on edge devices. Tech talk resources: https://github.com/Deeplite #ArmDevSummit #Deeplite #MachineLearning
*** Natural Language Processing Course: https://www.edureka.co/python-natural-language-processing-course *** This session on Context Free Grammar will give you a detailed and comprehensive knowledge of context-free grammar and how it is used in Natual Language Processing. It also focuses on Syntax trees and Techniques like Chinking and Chunking. ———————————— About this course : Edureka’s Natural Language Processing with Python course will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm. ———————————— Meetup: http://meetu.ps/c/4glvl/JzH2K/f Instagram: https://www.instagram.com/edureka_learning Slideshare: https://www.slideshare.net/EdurekaIN/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka For more information, please write back to us at sales@edureka.co or call us at: IND: 9606058406 / US: 18338555775 (toll free)
Dataset: https://github.com/laxmimerit/All-CSV-ML-Data-Files-Download In this video, we will learn about spam text message classification using NLP. Natural Language Processing (NLP) is the field of Artificial Intelligence, where we analyze 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. Tokenization is breaking the raw text into small chunks. Tokenization breaks the raw text into words, sentences called tokens. These tokens help in understanding the context or developing the model for the NLP. The tokenization helps in interpreting the meaning of the text by analyzing the sequence of the words. 🔊 Watch till last for a detailed description 03:33 What is NLP? 09:38 Natural Language generation 12:42 Installing packages 21:11 Bag of words 27:07 Get started with Code 32:05 Balance the data 37:16 Exploratory data analysis 49:08 Pipeline and random forest 58:41 Support vector machine 👇👇👇👇👇👇👇👇👇👇👇👇👇👇 ✍️🏆🏅🎁🎊🎉✌️👌⭐⭐⭐⭐⭐ 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 [More]
In this video we will try to understand how to use “Speech Recognition feature of C# “using “System.Speech.Recognition namespace”. The video provides explains how to acquire and monitor speech input, create speech recognition grammars that produce both literal and semantic recognition results, capture information from events generated by the speech recognition and, and configure and manage speech recognition engines.The complete video series of ADO.NET With Examples at..http://www.pluralsight.com/courses/adodotnet-by-example
This video contains a stepwise implementation of python code for object detection based on the OpenCV library. The following are the list of contents you will find inside the video. 1) basic understanding of object detection and image classification 2) installation of necessary libraries 2) line by line implementation for object detection using OpenCV a) Single Image b) Video.mp4 c) Live Webcam List of labels to download https://github.com/pjreddie/darknet/blob/master/data/coco.names Configuration file https://gist.github.com/dkurt/54a8e8b51beb3bd3f770b79e56927bd7