colab link ⭐ Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I’ve been using Kite for a few months and I love it! All Playlist In My channel Interview Playlist: Complete DL Playlist: Julia Playlist: Complete ML Playlist : Complete NLP Playlist: Docker End To End Implementation: Live stream Playlist: Machine Learning Pipelines: Pytorch Playlist: Feature Engineering : Live Projects : Kaggle competition : Mongodb with Python : MySQL With Python : Deployment Architectures: Amazon sagemaker : Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici Telegram link: Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more Connect with me here: Twitter: Facebook: instagram:
The implications and promises of artificial intelligence (AI) are unimaginable. Already, the now ubiquitous functions of AI have changed our lives dramatically—the “fastest route” always at our fingertips, a chatbot to answer all our questions. But what’s possible today will be dwarfed by the great potential of AI in the near future. Advances in computing and the existence of entirely new data sets are ushering in AI capable of realizing milestones that have long eluded us: curing cancer, exploring deep space, understanding climate change. That promise is what fuels our culture’s unrelenting excitement and investment in AI. It also raises the need for real, honest dialogue about how we build and adopt these technologies responsibly. This is the moment for such a conversation. How do we enforce human checks and balances on these machines? How do we educate a workforce whose jobs are evolving with AI? How do we make sure AI is accessible to all socioeconomic classes? The responsibility to raise these questions does not rest solely on the shoulders of journalists and leading technology companies. Rather, it’s the responsibility of all engaged citizens. The answers may not be readily available. But that cannot prevent us from asking them; the stakes are too high, and the promises of this technology are too great. Read more about how AI is shaping our world – From the World Economic Forum: From Hewlett Packard Labs:
Presented at Activate 2018 Slides: As the AI revolution continues to accelerate and new AI products are developed to solve key problems faced by consumers, businesses and the world at large. In the very near future, almost all new technology will incorporate some form of AI, driving the human machine engagement to unimaginable heights. As our reliance on AI deepens, many far-reaching ethical issues will arise – affecting everyone, including public citizens, small businesses utilizing AI or entrepreneurs developing the latest AI technology. We will discuss the moral code of AI, how we can solve some of the world’s largest problems with AI and being human in the age of AI. Learn more:
Here is the GitHub repository of the project:
In this tutorial, you’ll learn how to setup your NVIDIA Jetson Nano, run several object detection examples and code your own real-time object detection program in Python from a live camera feed. Several DNN models are supported, including SSD-Mobilenet and SSD-Inception, which are pre-trained on the 90-class MS COCO dataset and can detect a variety of objects.
5 Essential end to end data science projects for a data scientist resume. 3 of these projects are machine learning projects and 2 of them are power bi, tableau dashboarding BI projects. These are end to end data science, machine learning projects that will look very good on your resume. All of these projects are free and available on youtube along with the code. at 11:08 I have discussed important tips to generate new project ideas for data science and machine learning. ***This video is sponsored by Udemy, a popular e-learning platform. Get up to 80% off on your udemy course purchase by using below links, Udemy: Here are few courses that I recommend for learning Power BI and Tableau. Power BI Up and Running: Complete Power BI Intro: Tableau: (Note: I earn some affiliate commission when you buy above courses) 🤝 Support my youtube channel by buying a data science, coding 👕 T-shirt: ⭐️ Timestamps ⭐️ 00:00 Introduction 00:56 Power BI, Tableau project to generate sales insights 03:09 Power BI project for personal finances 04:28 Machine learning project: Classification 06:20 Machine learning project: Regression 08:58 Deep learning project in Tensorflow 11:08 3 Tips to generate data science project ideas Projects playlists: Sales insights (Power BI): Sales insights (Tableau): Personal finance dashboard (Power BI): Classification Project: Regression Project: Deep Learning Project: 🎥 Codebasics Hindi channel: #️⃣ Social Media #️⃣ 🔗 Discord: 📸 Instagram: 🔊 Facebook: [More]
Breaking the code: Alan Turing’s legacy in 2021 Ahead of the June 23 release into circulation of the new Turing £50 banknote (and Alan’s 109th birthday), The Alan Turing Institute is hosting a virtual lunchtime panel discussion exploring the life and legacy of Alan Turing to find out why he still means so much, to so many. Our speakers’ expertise range from Turing’s personal history, his work at Bletchley Park and his scientific legacy as one of the founding fathers of artificial intelligence and modern computing. #TuringLegacy Panellists: Sir Dermot Turing, Dr Shakir Mohamed (shakir_za), Dr Clara Barker (ClaraMBarker), Dr David Leslie, Professor Sue Black (Dr_Black), Chaired by Dr Kirstie Whitaker (@kirstie_j) Follow us on Twitter @turinginst Links: Closed captions – Event website – Slido (Q&A) – Events code of conduct – Contact – Join our mailing list – View and register for upcoming events –
Here we go over a Python Project using OpenCV and simple Machine Learning Google Colab Link : Support me on Patreon 💻 General Tech Dell Tower – Monitor - Keyboard – ​Mouse – ​Portable SSD – Headset – Airpods – 📸 Camera Gear Main Camera – Main Lens – Tripod – Jobi Tripod – Memory Card – 🎥Video Accessories Mic – Mic Arm – Writing Pad – Green Screen – LED lights – 👨‍💻Books I like on Personal Growth Compound Effect – Rework – Four Hour Work Week – Tools of Titans – The Last Lecture – Sam Walton – Originals – Blink – The Tipping Point – Rich Dad Poor Dad – 👨‍💻Books I like on Investing One up on Wall Street – Intelligent Investor – Common Sense Investing – DISCLOSURE: Some of the links on this page are affiliate links, meaning, at no additional cost to you, I may earn a commission if you click through and make a purchase. Affiliate commissions help fund videos like this one.
Try out Teachable Machine → Check out this blog → Creating an ML model seems like a complex and time-consuming task to complete, but it doesn’t have to be this way. In this episode of Making with Machine Learning, we show you how to easily create and train an ML model using Teachable Machines – Google Cloud’s no-code platform that trains ML models to recognize images, sounds, or poses. Watch to to learn how you can easily create an ML model with this tool! Chapters: 0:00 – Intro 0:25 – Train models to recognize letters 0:55 – Collecting training data 1:33 – Training the model 1:48 – Test model 2:13 – Conclusion Watch more episodes of Making with Machine Learning → Subscribe to get all the episodes as they come out → #MakingwithMachineLearning #MakingwithML Product: AI Platform Training; fullname: Dale Markowitz;
What You’ll Learn: – Introduction to Chatbot – Build your first intelligent conversational bots with no coding knowledge – Create topics from existing webpages – Improve your Chatbot using entities, variables, and topic redirects – Power Automate & other integrations – Chatbot optimization – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – — – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – As a thank you for watching our Learn with the Nerds: Power Virtual Agents conference, we put together a guidebook with everything you need to know about chatbots. We hope this book gives you a clear understanding of chatbots – it covers everything from how they’re created to all the benefits they can provide your business – and helps you get the most out of your chatbot experiences. Please, click on the link below to Download The Nerd’s Guide to Chatbots for FREE! – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – [More]
Is it possible to use machine learning without needing to code? The answer is yes! Uber’s AI lab recently open sourced python library called Ludwig that they’ve been using internally for 2 years. The tagline is that it allows anyone to use deep learning without coding. It will require some configuration and unix commands to setup, but I’ll show you how in this video. I’ll also talk about other code-free tools like Azure ML Studio, DataRobot, and DeepCognition. Enjoy! Code for this video: Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: instagram: Facebook: More learning resources: Join us at the School of AI: Join us in the Wizards Slack channel: Please support me on Patreon: Signup for my newsletter for exciting updates in the field of AI: Hit the Join button above to sign up to become a member of my channel for access to exclusive content! #MachineLearning #SirajRaval
Ever since Morse opened developer Tania Finlayson’s world, she’s been working to make it accessible for everyone. Interested in learning Morse code or using the keyboard Tania developed with the Gboard team? Visit
Watch how Microsoft Power Virtual Agents gives you a fast, intuitive and AI-rich way to create intelligent bots that make decisions and take actions. Join Emma Archer, from the Power Virtual Agents team, and Jeremy Chapman as they review. If you are new to Power Virtual Agents, it’s Microsoft’s newest member of the Power Platform. The Power Platform is Microsoft’s family of tools for low-to-zero-code modern app development, process automation, business insights, and now – chatbots. Interested in testing it out for yourself? Go to If you are unfamiliar with Microsoft Mechanics, we are Microsofts’ official video series for IT. You can watch and share valuable content and demos of current and upcoming tech from the people who build it at #Microsoft. Subscribe to our YouTube: Follow us on Twitter: Follow us on LinkedIn: Follow us on Facebook: #Microsoft #chatbot #PowerPlatform #PowerVirtualAgents #VirtualAgents
Practical fusion power, as the joke goes, has been “decades away…for decades.” But recent advancements in advanced algorithms and artificial intelligence promise to speed up the slow, slow progress towards a fusion-powered utopia. We visit one company that’s using machine learning to try and crack the code on fusion once and for all. Read more here: Subscribe: Reporter: Rachel Becker Producer: William Poor Director: Brennan King, Cory Zapatka Graphics: Alex Parkin Camera: Wes Reel Director of Audience Development: Ruben Salvadori Social Media Manager: Dilpreet Kainth Like Verge Science on Facebook: Follow on Twitter: Follow on Instagram: Read More: Community guidelines: Subscribe to Verge on YouTube for explainers, product reviews, technology news, and more:
Matt Zeiler is the CEO of Clarifai, a company that uses artificial intelligence and machine learning to recognize and identify different videos and images. While there are a lot of uses for image recognition — you’ve probably most recently interacted with facial recognition, for instance, on Facebook — Zeiler said online retail stands to benefit significantly from using AI. “You have to be thinking about it in your business,” Zeiler said at Recode’s Code Commerce event in New York. “This is going to change every interaction with your customers.” Watch his full presentation. — Subscribe: Check out our full video catalog: Follow Recode on Twitter: Follow Recode on Instagram: Read more:
Contact Best Phd Projects Visit us:
Speech Emotion Recognition System Matlab source code Speech emotion recognition is one of the latest challenges in speech processing. Besides human facial expressions speech has proven as one of the most promising modalities for the automatic recognition of human emotions. We have developed a fast and optimized algorithm for speech emotion recognition based on Neural Networks. We have tested code on Polish Emotional Speech. Database of Polish Emotional Speech comprises 240 recordings from 8 actors (4 females and 4 males). Recordings for every speaker were made during a single session. Each speaker utters five different sentences with six types of emotional load: joy, boredom, fear, anger, sadness and neutral (“no emotion”). Index Terms: Matlab, source, code, speech, emotion, recognition, human, computer, interaction. Reference URL:
The universe seems incredibly complex. But could its rules be dead simple? Juergen Schmidhuber’s fascinating story will convince you that this universe and your own life are just by-products of a very simple and fast program computing all logically possible universes. Juergen Schmidhuber is Director of the Swiss Artificial Intelligence Lab IDSIA (since 1995), Professor of Artificial Intelligence at the University of Lugano, Switzerland (since 2009), and Professor SUPSI (since 2003). He helped to transform IDSIA into one of the world’s top ten AI labs (the smallest!), according to the ranking of Business Week Magazine. His group pioneered the field of mathematically optimal universal AI and universal problem solvers. The algorithms developed in his lab won seven first prizes in international pattern recognition competitions, as well as several best paper awards. Since 1990 he has developed a formal theory of fun and curiosity and creativity to build artificial scientists and artists. He also generalized the many-worlds theory of physics to a theory of all constructively computable universes – an algorithmic theory of everything. He has published nearly 300 peer-reviewed scientific works on topics such as machine learning, artificial recurrent neural networks, fast deep neural nets, adaptive robotics, algorithmic information and complexity theory, digital physics, the formal theory of beauty & humor, and the fine arts. In 2008 he was elected member of the European Academy of Sciences and Arts. Schmidhuber’s overview web site on the simplest explanation of the universe, with his publications on all computable universes since 1996. [More]