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. 💻 Course website with code: http://spacy.pythonhumanities.com/ ✏️ Course developed by Dr. William Mattingly. Check out his channel: https://www.youtube.com/pythontutorialsfordigitalhumanities ⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Course Introduction ⌨️ (0:03:56) Intro to NLP ⌨️ (0:11:53) How to Install spaCy ⌨️ (0:17:33) SpaCy Containers ⌨️ (0:21:36) Linguistic Annotations ⌨️ (0:45:03) Named Entity Recognition ⌨️ (0:50:08) Word Vectors ⌨️ (1:05:22) Pipelines ⌨️ (1:16:44) EntityRuler ⌨️ (1:35:44) Matcher ⌨️ (2:09:38) Custom Components ⌨️ (2:16:46) RegEx (Basics) ⌨️ (2:19:59) RegEx (Multi-Word Tokens) ⌨️ (2:38:23) Applied SpaCy Financial NER 🎉 Thanks to our Champion and Sponsor supporters: 👾 Wong Voon jinq 👾 hexploitation 👾 Katia Moran 👾 BlckPhantom 👾 Nick Raker 👾 Otis Morgan 👾 DeezMaster 👾 AppWrite — Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
In this quick tutorial, we learn that machines can not only make sense of words but also make sense of words in their context. N-grams are one way to help machines understand a word in its context by looking at words in pairs. We go over what n-grams are and some examples of how you could use them in natural language processing. By looking at pairs of words, we capture the broader context of words to then train machines to learn these language queues and gain a better understanding of the real meaning of the text. — Learn more about Data Science Dojo here: https://datasciencedojo.com/data-science-bootcamp/ Watch the latest video tutorials here: https://tutorials.datasciencedojo.com/ See what our past attendees are saying here: https://datasciencedojo.com/bootcamp/reviews/#videos — Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo #machinelearning #datascience
Ever wondered how we can talk to machines and have them answer back? That is due to the magic of NLP. In this video, we will answer the question ‘What is NLP?’ for you. We will then look at some important steps involved in NLP all in 5 minutes! Don’t forget to take the quiz at 04:07! 🔥Free AI Course: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=NLPin5MinsScribe&utm_medium=Description&utm_source=youtube ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the AI & Machine Learning tutorial videos: https://www.youtube.com/watch?v=ad79nYk2keg&list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq #NaturalLanguageProcessing #NLP #NLPTutorialForBeginners #NaturalLanguageProcessingIn5Minutes #NLPTechniques #NLPTrainingVideos #NLPTutorial #NLPInArtificialIntelligence #NLPTraining #ArtificialIntelligence #MachineLearning #Simplilearn Post Graduate Program in AI and Machine Learning: Ranked #1 AI and Machine Learning course by TechGig Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and Machine Learning covers statistics, Python, machine learning, deep learning networks, NLP, and reinforcement learning. You will build and deploy deep learning models on the cloud using AWS SageMaker, work on voice assistance devices, build Alexa skills, and gain access to GPU-enabled labs. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU enabled Labs ✅ 450+ hours of Applied learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program [More]
In this video we will understand the detailed explanation of Lemmatization and understand how it can be used in Natural Language Processing. We will also see the basic difference between Lemmatization and stemming. NLP playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm If you want to Give donation to support my channel, below is the Gpay id GPay: krishnaik06@okicici Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
I’ve designed a free natural language processing curriculum for anyone interested in improving their skills in order to start a startup, get consulting work, or find full-time work related to NLP. This curriculum is for beginners and starts with basic NLP terminology, then moves into basic language models and word embeddings. Then, it moves onto more advanced concepts like neural networks, sequence modeling and dialogue systems. At the end, I’ll detail what the most experimental, modern-day techniques are in the field. I hope you find this curriculum useful! Curriculum for this video: https://github.com/llSourcell/Learn-Natural-Language-Processing-Curriculum Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Prerequisites are here: – Learn Python https://www.edx.org/course/introduction-to-python-fundamentals-4 – Statistics http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf – Probability https://static1.squarespace.com/static/54bf3241e4b0f0d81bf7ff36/t/55e9494fe4b011aed10e48e5/1441352015658/probability_cheatsheet.pdf – Calculus http://tutorial.math.lamar.edu/pdf/Calculus_Cheat_Sheet_All.pdf – Linear Algebra https://www.souravsengupta.com/cds2016/lectures/Savov_Notes.pdf The rest of the curriculum is in the github link above, check it out! Make Money with Tensorflow 2.0: https://www.youtube.com/watch?v=WS9Nckd2kq0 Watch Me Build a Finance Startup: https://www.youtube.com/watch?v=oeraUtRgsbI Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Hit the Join button above to sign up to become a member of my channel for access to exclusive live streams! Join us at the School of AI: https://theschool.ai/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w And please support me on Patreon: https://www.patreon.com/user?u=3191693
This course is a practical introduction to natural language processing with TensorFlow 2.0. In this tutorial you will go from having zero knowledge to writing an artificial intelligence that can compose Shakespearean prose. No prior experience with deep learning is required, though it is always helpful to have more background information. We’ll use a combination of embedding layers, recurrent neural networks, and fully connected layers to perform the classification. ⭐️Course Contents ⭐️ ⌨️ (01:16) Getting Started with Word Embeddings ⌨️ (33:25) How to Perform Sentiment Analysis on Movie Reviews ⌨️ (59:32) Let’s Write An AI That Writes Shakespeare ⭐️Course Description ⭐️ The basic idea behind natural language processing is that we start out with words, i.e. strings of characters, that are almost impossible for the computer to meaningfully parse. We can transform these strings into a vector in a higher dimensional space. Different words will be represented as vectors of different lengths and directions in this space, and this allows us to find relationships between words by finding the component of one vector along another. Don’t worry, the TensorFlow library handles all of this, we just have to have some basic idea of how it works. Since this is a type of supervised learning, we also have labels for our text. This allows the AI to compare the relationships between words to the training labels, and learn which sequences of words represent good and bad movie reviews. This would also work for finding toxic comments, fake product reviews… just about [More]
Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, California, on the shores of Lake Merritt: https://scale.bythebay.io. Join us! —– In this talk, I will describe deep learning algorithms that learn representations for language that are useful for solving a variety of complex language problems. I will focus on 3 tasks: Fine-Grained sentiment analysis; Question answering to win trivia competitions (like Whatson’s Jeopardy system but with one neural network); Multimodal sentence-image embeddings (with a fun demo!) to find images that visualize sentences. I will also show some demos of how deepNLP can be made easy to use with MetaMind.io’s software. Richard Socher is the CTO and founder of MetaMind, a startup that seeks to improve artificial intelligence and make it widely accessible. He obtained his PhD from Stanford working on deep learning with Chris Manning and Andrew Ng. He is interested in developing new AI models that perform well across multiple different tasks in natural language processing and computer vision. He was awarded the 2011 Yahoo! Key Scientific Challenges Award, the Distinguished Application Paper Award at ICML 2011, a Microsoft Research PhD Fellowship in 2012 and a 2013 ‘Magic Grant’ from the Brown Institute for Media Innovation and the 2014 GigaOM Structure Award.
Machine learning is everywhere in today’s NLP, but by and large machine learning amounts to numerical optimization of weights for human designed representations and features. The goal of deep learning is to explore how computers can take advantage of data to develop features and representations appropriate for complex interpretation tasks. This tutorial aims to cover the basic motivation, ideas, models and learning algorithms in deep learning for natural language processing. Recently, these methods have been shown to perform very well on various NLP tasks such as language modeling, POS tagging, named entity recognition, sentiment analysis and paraphrase detection, among others. The most attractive quality of these techniques is that they can perform well without any external hand-designed resources or time-intensive feature engineering. Despite these advantages, many researchers in NLP are not familiar with these methods. Our focus is on insight and understanding, using graphical illustrations and simple, intuitive derivations.
This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines. – Natural Language Processing (Part 1): Introduction to NLP & Data Science – Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python – Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python – Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python – Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python – Natural Language Processing (Part 6): Text Generation with Markov Chains in Python All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial
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
A word embedding is a learned representation for text where words that have the same meaning have a similar representation. It is this approach to representing words and documents that may be considered one of the key breakthroughs of deep learning on challenging natural language processing problems. 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 If you want to Give donation to support my channel, below is the Gpay id GPay: krishnaik06@okicici Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
Talk by Ekaterina Kochmar, University of Cambridge, at the Cambridge Coding Academy Data Science Bootcamp: https://cambridgecoding.com/datascience-bootcamp
Learn from experts how to succeed with AI and automation. Watch the full recording of UiPath Live! https://bit.ly/3aIXwl7 See Robotic Process Automation (RPA) in action with this end-to-end invoice automated workflow powered by UiPath. Watch the robot performing the following actions: – monitoring and reading invoices in a PDF format, – extracting key information, – opening and filling in invoice details in SAP, – sending email notifications, as well as other background activities. Discover more about what #RPA can do for your #Finance & Accounting department -http://bit.ly/2NoHnH4. 🚀Join our community for more updates: Blog – https://www.uipath.com/blog LinkedIn – https://www.linkedin.com/company/uipath/ Twitter – https://twitter.com/UiPath Facebook – https://www.facebook.com/UiPath Connect! – https://connect.uipath.com/ #automate #invoiceprocessing
Now that we understand some of the basics of of natural language processing with the Python NLTK module, we’re ready to try out text classification. This is where we attempt to identify a body of text with some sort of label. To start, we’re going to use some sort of binary label. Examples of this could be identifying text as spam or not, or, like what we’ll be doing, positive sentiment or negative sentiment. Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Natural Language Processing (NLP) is a field of computer science that aims to understand or generate human languages, either in text or speech form. Computers are programmed to identify written and spoken words. But to really communicate with people, they need to understand context. Learn more: https://accntu.re/2MX0rwT #NaturalLanguageProcessing #NLP #AI
Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry — we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney (@lmoroney). In this first lesson we’ll talk about how to represent words in a way that a computer can process them, with a view to later training a neural network to understand their meaning. Hands-on Colab → https://goo.gle/2uO6Gee NLP Zero to Hero playlist → https://goo.gle/nlp-z2h Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow
http://en.triowin.com/citrus-processingline-15266140703740335.html Shanghai Triowin Intelligent Machinery Co., Ltd import the most advanced technology from Italy, Europe and America, form brilliant technical program for citrus processing line. Customized design is available based on the investment and actual production situations of enterprises, realize real turn-key project for customer. Triowin has been engaging in manufacturing citrus processing machinery for more than 19 years. Benefited from experience of more than 120 fruit processing lines, we are able to design, manufacture and engineer citrus processing line, capacity ranging from 60 to 2,000 TPD. The high quality, life-cycle and after-sales service are highly recognized and appreciated through our worldwide customers. Website: en.triowin.com E-mail:info@trowin.com WhatsApp:18017912901 WeChat:18917060295 TEL. :0086-21-37901188 FAX.:0086-21-54331011 Address:No.5899 Tingwei Rd.Jinshan Industrial Zone,shanghai, China 201506
This video covers Stanford CoreNLP Example. GitHub link for example: https://github.com/TechPrimers/core-nlp-example Stanford Core NLP: https://stanfordnlp.github.io/CoreNLP/ Stanford API example: https://stanfordnlp.github.io/CoreNLP/api.html Slack Community: https://techprimers.slack.com Twitter: https://twitter.com/TechPrimers Facebook: http://fb.me/TechPrimers GitHub: https://github.com/TechPrimers or https://techprimers.github.io/ Video Editing: iMovie Intro Music: A Way for me (www.hooksounds.com) #CoreNLP #TechPrimers
Transfer Learning in Natural Language Processing (NLP): Open questions, current trends, limits, and future directions. Slides: https://tinyurl.com/FutureOfNLP A walk through interesting papers and research directions in late 2019/early-2020 on: – model size and computational efficiency, – out-of-domain generalization and model evaluation, – fine-tuning and sample efficiency, – common sense and inductive biases. by Thomas Wolf (Science lead at HuggingFace) HuggingFace on Twitter: https://twitter.com/huggingface Thomas Wolf on Twitter: https://twitter.com/Thom_Wolf
Download: The circuit diagram and Project programming can be downloaded by clicking on the link below Arduino Image Processing based Entrance lock Control System Download Libraries: https://www.electroniclinic.com/arduino-libraries-download-and-projects-they-are-used-in-project-codes/ Image Processing based Eyepupil Tracking: https://youtu.be/xQrTNoSgNDQ Human machine tracking using image processing: https://youtu.be/HnKRy26NXMU Watch other tutorials: 9: Image processing based entrance control system https://youtu.be/TYllIMfJ3Eg 8: GSM and GPS based car accident location monitoring https://youtu.be/tumEQioxT6I 7: GSM based GAS leakage detection and sms alert https://youtu.be/Ar4LowNT_HI 6: Wireless Tongue controlled wheelchair https://youtu.be/WNCn062YzXc 5: Human Posture Monitoring System https://youtu.be/6bxZyTi6m-4 4: RFID based bike anti theft system https://youtu.be/iGtu6TQ-_ao 3: RFID based students attendance system https://youtu.be/gc4LLN1vftk 2: Piezo Electric generator https://youtu.be/n6FFnJVq5cQ 1: iot car parking monitoring system https://youtu.be/tjLAjGi6O5Q Support me on Patreon and get access to hundreds of projects: https://www.patreon.com/ElectroniClinic Amazon Free Unlimited reading and unlimited listening on any device. sign up for free account and have access to thousands of Programming and hardware designing books. https://amzn.to/2LWmxOg *********** free Amazon Business Account: Sign up for Amazon Business account https://amzn.to/2MiPiBT ************ Project Description: ******************** This is a very detailed tutorial on how to make image processing based human recognition system for entrance controlling. In this project we will be using Arduino uno for controlling the electronic door lock, The Arduino will receive command from the vb.net application when a human will be detected. We will be using xml file for human face detection. This xml file will be used in vb.net application to track a human face. The application designed in vb.net visual basic make use of the emguCv. [More]
Crazy Cake Making Machines AWESOME FOOD PROCESSING | Amazing Cake Automated Processing Machines in Factory – Cream Cake, Cheese Cake & Chocolate Cake #Satkahon #Food #Technology #Factory ————————————————————— Video Credit: Unifiller www.unifiller.com +1 888 733 8444 ————————————————————— Music: Track: Diviners – Savannah (feat Philly K) [NCS Release] Music provided by NoCopyrightSounds. Free Download / Stream: http://ncs.io/savannah Watch: https://www.youtube.com/watch?v=u1I9ITfzqFs Track: Marin Hoxha – Endless [NCS Release] Music provided by NoCopyrightSounds. Free Download / Stream: http://ncs.io/Endless Watch: https://www.youtube.com/watch?v=Hj5oPx_FiYk Track: Unknown Brain – Superhero (feat. Chris Linton) [NCS Release] Music provided by NoCopyrightSounds. Free Download / Stream: http://ncs.io/superhero Watch: https://www.youtube.com/watch?v=LHvYrn3FAgI
For more information go to https://curiositystream.com/crashcourse So far in this series, we’ve mostly focused on how AI can interpret images, but one of the most common ways we interact with computers is through language – we type questions into search engines, use our smart assistants like Siri and Alexa to set alarms and check the weather, and communicate across language barriers with the help of Google Translate. Today, we’re going to talk about Natural Language Processing, or NLP, show you some strategies computers can use to better understand language like distributional semantics, and then we’ll introduce you to a type of neural network called a Recurrent Neural Network or RNN to build sentences. Crash Course AI is produced in association with PBS Digital Studios https://www.youtube.com/user/pbsdigitalstudios/videos Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Zach Van Stanley, Jennifer Killen, Nathan Catchings, Brandon Westmoreland, dorsey, Kenneth F Penttinen, Trevin Beattie, Erika & Alexa Saur, Justin Zingsheim, Jessica Wode, Tom Trval, Jason Saslow, Nathan Taylor, Khaled El Shalakany, SR Foxley, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, David Noe, Shawn Arnold, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore — Want to find Crash Course elsewhere on the internet? Facebook – http://www.facebook.com/YouTubeCrashCourse Twitter – [More]
Natural language processing (Wikipedia): “Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages