Looking for a career upgrade & a better salary? We can help, Choose from our no 1 ranked top programmes. 25k+ career transitions with 400 + top corporate companies. Exclusive for working professionals: https://glacad.me/3ysSqDM 🔥 Get the free certificate of completion for the Artificial Intelligence With Python Course, Register Now: https://glacad.me/3pRBkvC People skilled in Artificial Intelligence are paid around $150k per annum. Top companies such as Google, Facebook, Apple, and Microsoft invest heavily in the R&D of their Artificial Intelligence systems. Keeping the importance of artificial intelligence in mind, we have come up with this full course on Artificial Intelligence. Visit Great Learning Academy, for free access to full courses, projects, data sets, codebooks & live sessions: https://glacad.me/3k19Wrx ————————————————————————————————————————————————————- This session will be taken by Professor Mukesh Rao, who is the Director of Education Data Science at Great Learning. Professor Mukesh Rao has over 20 years of industry experience in Data Science, Market Research and Project Management and has conducted over 100 corporate trainings. ————————————————————————————————————————————————————- These are the topics covered in this Artificial Intelligence Tutorial: *Introduction – 00:00:00 *History Behind Deep Neural Networks – 00:02:02 *Relationship between Biological Neuron and Artificial Neuron – 00:08:05 *Working of Perceptron – 00:018:05 Demo on McCullohPitt and Rosenblat Neurons-00:55:34 *Architecture of Artificial Neural Network- 01:17:35 *Activation Functions – 02:20:11 *Demo on Wine Dataset using Keras Sequential Model – 03:35:00 *Back-propagation and Gradient Descent Algorithm -06:13:00 *Demo on MNIST Dataset – 6:44:55 ——————————————————————————————————– Visit Great Learning Academy, to get access to 80+ free courses with [More]
In our SERIES FINALE of Crash Course Computer Science we take a look towards the future! In the past 70 years electronic computing has fundamentally changed how we live our lives, and we believe it’s just getting started. From ubiquitous computing, artificial intelligence, and self-driving cars to brain computer interfaces, wearable computers, and maybe even the singularity there is so much amazing potential on the horizon. Of course there is also room for peril with the rise of artificial intelligence and more immediate displacement of much of the workforce through automation. It’s tough to predict how it will all shake out, but it’s our hope that this series has inspired you to take part in shaping that future. Thank you so much for watching. 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
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
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]
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** Machine Learning Training with Python: https://www.edureka.co/machine-learning-certification-training ** This Edureka video on ‘Mathematics for Machine Learning’ teaches you all the math needed to get started with mastering Machine Learning. It teaches you all the necessary topics and concepts of Linear Algebra, Multivariate Calculus, Statistics, and Probability and also dives into the actual implementation of these topics. Blog Link: https://bit.ly/2PX5lIp Check out our playlist for more videos: http://bit.ly/2taym8X —————————————————————————— Subscribe to our channel to get video updates: https://bit.ly/2PYu1jD Hit the subscribe button above. 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/ SlideShare: https://www.slideshare.net/EdurekaIN/ #Edureka #MachineLearning #MathematicsForMachineLearning # —————————————————————————— How does it work? 1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work 2. 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. 3. At the end of the training, you will be working on a real-time project for which we will provide you with a Grade and a Verifiable Certificate! —————————————————————————— About the Course Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in Python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You [More]
Do you want to become a 6-figure developer with Python? Check out the best Python course on the planet 👉 https://course.profitableprogrammer.co/pp-2019?utm_source=youtube&utm_medium=yt-description&utm_content=python-ai-tutorial&utm_campaign=pwp If you want to enroll in an EPIC Beginner Python course where you can have exercises and projects all under one account & for FREE… Click this link: https://cleverprogrammer.teachable.com/p/learn-python ⭐ Join the BEST Discord Community for Developers on the planet 👉 https://discord.gg/7nazyQUSNe Time Stamps 👇 … ENJOY🔥 3:02 – Face Detector App 2:08:42 – Self Driving Car App 4:11:47 – Smile Detector App 6:47:03 – TensorFlow Image Classifier App -Qazi
🔥 Enrol for FREE Cloud Computing Course & Get your Completion Certificate: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=Skillup-CloudComputing&utm_medium=DescriptionFirstFold&utm_source=youtube The Google Cloud Platform Tutorial video will cover all the important concepts of Google Cloud Platform. Google Cloud Platform is a set of cloud computing services provided by Google that runs on the same infrastructure that Google uses for its end-user products like, YouTube, Gmail and more. In this video, we will be looking into what is GCP? GCP tutorial, AWS vs GCP, GCP web hosting, Google cloud ML, GCP fundamentals, Google Cloud Platform Fundamentals (CP100A) Certification Training. Below are the topics we will be discussing in the video today: 00:00:00 What is GCP? 01:32:37 GCP Tutorial 03:08:50 AWS vs GCP 03:17:03 GCP Web hosting 03:36:14 Google Cloud ML 03:38:38 GCP Fundamentals (CP100A) Certification Training ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Google Cloud Platform(GCP) tutorial videos: https://bit.ly/35r8IPg #GoogleCloudPlatformTutorial #GoogleCloudPlatoformFullCourse #GoogleCloudTraining #GoogleCloudPlatformTutorialForBeginners #GoogleCloudCertification #GoogleCloudTutorial #GCPTutorial #Simplilearn Simplilearn’s Google Cloud Platform (GCP) Architect certification program will empower you with the skills needed to advance your career in cloud architecture and become a certified Google Professional Cloud Architect. The course covers IAM, Networking, cloud storage, and much more. Simplilearn’s online Google Cloud Platform (GCP) Architect certification course introduces you to the flexible infrastructure and platform services provided by Google Cloud Platform. In this course, you will learn how to analyze and deploy infrastructure components such as networks, storage systems, and application services. Key Features: 1. 100% Money Back Guarantee 2. [More]
This video on Artificial Intelligence Full Course will help us understand the basics of artificial intelligence. We will look at the future of AI and listen to some of the industry experts and learn what they have to say about AI. You will see the top 10 applications of AI in 2021. Then, we will understand Machine Learning and Deep Learning and the different algorithms used to build AI models. Finally, you will learn the Top 10 Artificial Intelligence Technologies In 2021. Let’s begin! 🔥Enroll for Free Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=AI&utm_medium=Description&utm_source=youtube 00:00:00 Artificial Intelligence in 5 min 00:05:59 Future Of Artificial Intelligence 00:13:20 Artificial Intelligence Application 2021 00:25:38 Should we be afraid of Artificial Intelligence 00:38:21 What is Artificial Intelligence 00:48:13 Machine Learning Part 1 01:21:57 Linear Regression Analysis 01:41:34 Decision Tree 01:58:12 Machine Learning Part 2 02:51:14 KNN algorithm Using Python 03:17:40 Mathematics For Machine Learning 05:07:53 Deep Learning Tutorial 05:52:46 TensorFlow 2.0 Tutorial for Beginners 07:18:44 Top 10 Artificial Intelligence Technologies in 2021 ✅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 #ArtificialIntelligenceCourse #ArtificialIntelligenceTutorial #ArtificialIntelligenceFullCourse #AIFullCourse #AIForBeginners #ArtificialIntelligenceTutorialForBeginners #Simplilearn What is Artificial Intelligence? Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. AI has made significant advances in the past few years and has impacted both our everyday lives and business in big ways. [More]
Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence. Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning. Each of these modules include in-depth explanations and a variety of different coding examples. After completing this course you will have a thorough knowledge of the core techniques in machine learning and AI and have the skills necessary to apply these techniques to your own data-sets and unique problems. ⭐️ Google Colaboratory Notebooks ⭐️ 📕 Module 2: Introduction to TensorFlow – https://colab.research.google.com/drive/1F_EWVKa8rbMXi3_fG0w7AtcscFq7Hi7B#forceEdit=true&sandboxMode=true 📗 Module 3: Core Learning Algorithms – https://colab.research.google.com/drive/15Cyy2H7nT40sGR7TBN5wBvgTd57mVKay#forceEdit=true&sandboxMode=true 📘 Module 4: Neural Networks with TensorFlow – https://colab.research.google.com/drive/1m2cg3D1x3j5vrFc-Cu0gMvc48gWyCOuG#forceEdit=true&sandboxMode=true 📙 Module 5: Deep Computer Vision – https://colab.research.google.com/drive/1ZZXnCjFEOkp_KdNcNabd14yok0BAIuwS#forceEdit=true&sandboxMode=true 📔 Module 6: Natural Language Processing with RNNs – https://colab.research.google.com/drive/1ysEKrw_LE2jMndo1snrZUh5w87LQsCxk#forceEdit=true&sandboxMode=true 📒 Module 7: Reinforcement Learning – https://colab.research.google.com/drive/1IlrlS3bB8t1Gd5Pogol4MIwUxlAjhWOQ#forceEdit=true&sandboxMode=true ⭐️ Course Contents ⭐️ ⌨️ (00:03:25) Module 1: Machine Learning Fundamentals ⌨️ (00:30:08) Module 2: Introduction to TensorFlow ⌨️ (01:00:00) Module 3: Core Learning Algorithms ⌨️ (02:45:39) Module 4: Neural Networks with TensorFlow ⌨️ (03:43:10) Module 5: Deep Computer Vision – Convolutional Neural Networks ⌨️ (04:40:44) Module 6: Natural Language Processing with RNNs ⌨️ (06:08:00) Module 7: Reinforcement Learning with Q-Learning ⌨️ (06:48:24) Module 8: Conclusion and Next Steps [More]
🔵Edureka Python Programming Certification Course (Use Code “𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎”): https://www.edureka.co/python-programming-certification-training This Edureka video on Python Full Course will help you learn the Python programming language and its core concepts with examples from scratch. Below are the topics covered in this Python tutorial video: 00:00 Introduction 01:55 What is Python? 03:40 Why is Python popular? 04:55 Features of Python 6:50 Where is Python used in the industry? 7:50 Learning Path 9:15 Career Opportunities 10:30 How Netflix use Python? 11:55 How does it use Python? 18:15 Python Developer Salary 18:50 Who is Python Developer? 19:20 Python Developer Job Trends 21:55 How to become a Python Developer? 23:05 Who is a Python developer? 33:50 Job Roles 41:40 Emerging Job Roles 44:30 Road Map 47:05 Python Installation 54:30 How to run a Python program? 58:35 Best IDE for Python 59:35 What is an IDE? 59:50 Features of an IDE 1:00:50 Best IDEs of Python 1:07:40 PyCharm Tutorial 1:07:42 Introduction to PyCharm 1:09:07 Features of PyCharm 1:28:02 Comments in Python 1:28:52 What are Comments? 1:29:47 When to use Python? 1:30:22 How to write comments in Python? 1:32:22 Types of Comments 1:35:57 Docstring Comments 1:39:02 Variables & Data Types 1:39:17 Variable definition & Declaration 1:41:22 Data Types 1:41:42 Numbers 1:43:12 String 1:46:02 List 1:48:12 Dictionary 1:50:12 Tuple 1:51:27 Set 1:53:52 Type Conversion 1:54:42 Python Collections 1:57:12 Specialised Collections Data Types 2:14:57 Arrays 2:15:32 What is an Array? 2:17:27 How to create Arrays in Python? 2:20:52 Accessing Array Elements 2:22:42 Basic Array Operations 2:24:27 Adding elements to an [More]
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
Deep learning is a revolutionary technique for discovering patterns from data. We’ll see how this technology works and what it offers us for computer graphics. Attendees learn how to use these tools to power their own creative and practical investigations and applications.
Take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program. Learn more at: https://stanford.io/2rf9OO3 Professor Christopher Potts & Consulting Assistant Professor Bill MacCartney, Stanford University http://onlinehub.stanford.edu/ Professor Christopher Potts Professor of Linguistics and, by courtesy, Computer Science Director, Stanford Center for the Study of Language and Information http://web.stanford.edu/~cgpotts/ Consulting Assistant Professor Bill MacCartney Senior Engineering Manager, Apple https://nlp.stanford.edu/~wcmac/ To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224u/ To get the latest news on Stanford’s upcoming professional programs in Artificial Intelligence, visit: http://learn.stanford.edu/AI.html To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu
This video on the Artificial Intelligence tutorial will make you learn in detail about the different concepts involved in AI. First, you will understand the basics of AI. Since AI is a combination of Machine Learning and Deep Learning, you will learn about Machine Learning with hands-on demo. Then, you will get an idea about the top 10 applications of Machine Learning. This tutorial will also help you learn about Deep Learning in Python using TensorFlow. You will come across some essential Deep Learning applications. Finally, you will learn how to become an AI Engineer and look at some vital machine learning and deep learning interview questions. Now, let’s dive in and learn artificial intelligence in detail. 🔥Free Artificial Intelligence Course: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=AI&utm_medium=Description&utm_source=youtube Below topics are explained in this Artificial Intelligence tutorial: 1. Introduction to Artificial Intelligence (0:33) 2. What is Artificial Intelligence (06:20) 3. Brief history of Artificial Intelligence (07:16) 4. Types of Artificial Intelligence (10:25) 5. Artificial of Artificial Intelligence (13:23) 6. Future of Artificial Intelligence (14:56) 7. Machine Learning vs Deep Learning vs Artificial Intelligence (16:15) 8. Human vs Artificial Intelligence (19:36) 9. What is Machine Learning and Deep Learning? (21:33) 10. Real-life examples (31:31) 11. Types of Artificial Intelligence (33:49) 12. Machine Learning tutorial (42:38) 13. Why Machine Learning (43:12) 14. What is Machine Learning (47:19) 15. Types of Machine Learning (54:01) 16. Supervised Learning (54:13) 17. Reinforcement Learning (56:35) 18. Supervised vs Unsupervised (57:54) 19. Machine Learning Algorithms (59:12) 20. Linear regression (1:01:00) 21. Decision trees [More]
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Artificial Intelligence in Hindi | Free Course by Google | Machine Learning | Career, Scope Google Free Course – https://ai.google/education/ EDUCATIONAL VIDEOS [हिंदी में ] ►Countries where Education is free for Indians | दुनिया के ऐसे देश जहां Education फ्री है✔https://www.youtube.com/watch?v=qDNG6H5qRA0&t=2s ► Right Attitude Motivation For Students | Power of Positive thinking in hindi ✔ https://www.youtube.com/watch?v=cmVvZb6b5VE ► What is Investment Banking in HINDI || Investment Banker ? ✔ https://www.youtube.com/watch?v=tMYVaPFG4Kw ► Fastest and Easiest Way to Learn English || ENGLISH Sikhne ka Aasan tarika ✔ https://www.youtube.com/watch?v=GF5OHAZcW0k ► How to Get Education LOAN in INDIA 2017 ✔ https://www.youtube.com/watch?v=DoluUHBZ1zw. ► MBA INDIA VS MBA ABROAD – WHICH IS BEST ? ✔ https://www.youtube.com/watch?v=ufgd8pkvtjE ► Highest Paying Jobs in India 2017✔ https://www.youtube.com/watch?v=zAa0w1eufLs Follow us on : Facebook – https://www.facebook.com/PraveenDilliwala Twitter – https://twitter.com/praveendiliwala Instagram – https://www.instagram.com/praveendilliwala Subscribe Here- https://www.youtube.com/PraveenDilliwala
Check out my collab with “Above the Noise” about Deepfakes: https://www.youtube.com/watch?v=Ro8b69VeL9U Today, we’re going to talk about five common types of algorithmic bias we should pay attention to: data that reflects existing biases, unbalanced classes in training data, data that doesn’t capture the right value, data that is amplified by feedback loops, and malicious data. Now bias itself isn’t necessarily a terrible thing, our brains often use it to take shortcuts by finding patterns, but bias can become a problem if we don’t acknowledge exceptions to patterns or if we allow it to discriminate. Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios 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, Efrain R. Pedroza, Matthew Curls, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, 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, William McGraw, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore — Want to find Crash Course elsewhere on the internet? Facebook – http://www.facebook.com/YouTubeCrashCourse 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 #CrashCourse #ArtificialIntelligence #MachineLearning
In this video we discuss:- 1- Which type of student’s should opt for the AI course 2- Areas of application of AI. 3- Future jobs in AI. Kindly Watch our part# 1 as well.
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]
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Natural Language Processing , Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English. Natural Language Understanding (NLU) Natural Language Generation (NLG)
This video shows how we can use Break and Continue statements in a loop to effectively handle exceptions. ——————————————————- *About us* Applied AI course (AAIC Technologies Pvt. Ltd.) is an Ed-Tech company based out in Hyderabad offering on-line training in Machine Learning and Artificial intelligence. Applied AI course through its unparalleled curriculum aims to bridge the gap between industry requirements and skill set of aspiring candidates by churning out highly skilled machine learning professionals who are well prepared to tackle real world business problems. *Key highlights of Applied AI course* 1. Job guarantee or money back guarantee 2. Query resolution inside 24 hours 3. Personalized learning path for every course participant 4. 30 Practical Assignments 5. 15 end-to-end case studies based on real world problems across various industries 6. Mentor-ship for portfolio development, resume and interview preparation, and career counseling for every course participant For More information Please visit https://www.appliedaicourse.com/ For any queries you can either drop a mail to team@appliedaicourse.com or call us at +91 8106-920-029 or +91 6301-939-583 Facebook: https://www.facebook.com/appliedaicou… Soundcloud: https://soundcloud.com/applied-ai-course Twitter: https://twitter.com/appliedaicourse #AppliedAICourse,#Python,#BreakContinueStatements,#ArtificialIntelligence,#MachineLearning,#DeepLearning,#DataScience,#NLP,#AI,#ML
🔥 Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training This Edureka Machine Learning Full Course video will help you understand and learn Machine Learning Algorithms in detail. This Machine Learning Tutorial is ideal for both beginners as well as professionals who want to master Machine Learning Algorithms. Below are the topics covered in this Machine Learning Tutorial for Beginners video: 00:00 Introduction 2:47 What is Machine Learning? 4:08 AI vs ML vs Deep Learning 5:43 How does Machine Learning works? 6:18 Types of Machine Learning 6:43 Supervised Learning 8:38 Supervised Learning Examples 11:49 Unsupervised Learning 13:54 Unsupervised Learning Examples 16:09 Reinforcement Learning 18:39 Reinforcement Learning Examples 19:34 AI vs Machine Learning vs Deep Learning 22:09 Examples of AI 23:39 Examples of Machine Learning 25:04 What is Deep Learning? 25:54 Example of Deep Learning 27:29 Machine Learning vs Deep Learning 33:49 Jupyter Notebook Tutorial 34:49 Installation 50:24 Machine Learning Tutorial 51:04 Classification Algorithm 51:39 Anomaly Detection Algorithm 52:14 Clustering Algorithm 53:34 Regression Algorithm 54:14 Demo: Iris Dataset 1:12:11 Stats & Probability for Machine Learning 1:16:16 Categories of Data 1:16:36 Qualitative Data 1:17:51 Quantitative Data 1:20:55 What is Statistics? 1:23:25 Statistics Terminologies 1:24:30 Sampling Techniques 1:27:15 Random Sampling 1:28:05 Systematic Sampling 1:28:35 Stratified Sampling 1:29:35 Types of Statistics 1:32:21 Descriptive Statistics 1:37:36 Measures of Spread 1:44:01 Information Gain & Entropy 1:56:08 Confusion Matrix 2:00:53 Probability 2:03:19 Probability Terminologies 2:04:55 Types of Events 2:05:35 Probability of Distribution 2:10:45 Types of Probability 2:11:10 Marginal Probability 2:11:40 Joint Probability 2:12:35 Conditional Probability 2:13:30 Use-Case 2:17:25 Bayes Theorem [More]
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