Applied Artificial Intelligence

This video is a detailed walk-through of Applied Machine learning course. ------------------------------------------------------- *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#AboutTheCourse #ArtificialIntelligence,#MachineLearning,#DeepLearning,#DataScience,#NLP,#AI,#ML

? KnowledgeGate Website: https://www.knowledgegate.ai For free notes on University exam’s subjects, please check out our course: https://www.knowledgegate.ai/courses/FREE-SEMESTER-EXAM-BUNDLE ? Please message us on WhatsApp: https://wa.me/918000121313 ? Contact Us: ? ?Call on: +91-8000121313 ? Telegram Updates: https://t.me/kg_gate ? Whatsapp Updates: https://www.whatsapp.com/channel/0029VaC5Weq2Jl85NaTls63w ? Email: contact@knowledgegate.in ? One Shot Complete Playlist for GATE CSE Exam : ? ?? http://tiny.cc/GATEoneshotplaylist ? Our One Shot Semester Exam Videos: ? ? Operating System: https://youtu.be/xw_OuOhjauw ? DBMS: https://youtu.be/YRnjGeQbsHQ ? Computer Network: https://youtu.be/q3Z3Qa1UNBA ? Digital Electronics: https://youtu.be/pHNbm-4reIc ? Computer Architecture: https://youtu.be/DsK35f8wyUw ? Data Structure: https://youtu.be/MdG0Vw9f1A4 ? Algorithm: https://youtu.be/z6DY_YSdyww ? Software Engineering: https://youtu.be/NlLM3sVF8wY ? Theory of Computation: https://youtu.be/9kuynHcM3UA ? Compiler: https://youtu.be/OQCjakjCJu4 ? Discrete Maths: https://youtu.be/3zOtLEeHygg ? Artificial Intelligence: https://youtu.be/yiXAmkimZRQ ? Machine Learning: https://youtu.be/2oGsCHlfBUg #knowledgegate #sanchitsir #sanchitjain ******************************************************* ** Content in this video: 00:00 Chapter-0 (About this video) 02:04 Chapter-1 (INTRODUCTION) 1:01:36 Chapter-2 (PROBLEM SOLVING METHODS) 3:21:47 Chapter-3 (KNOWLEDGE REPRESENTATION) 4:34:06 Chapter-4 (SOFTWARE AGENTS) 5:08:56 Chapter-5 (APPLICATIONS) Chapter-1 (INTRODUCTION): Introduction-Definition - Future of Artificial Intelligence - Characteristics of Intelligent Agents - Typical Intelligent Agents - Problem Solving Approach to Typical Al problems. Chapter-2 (PROBLEM SOLVING METHODS): Problem solving Methods - Search Strategies- Uninformed - Informed - Heuristics - Local Search Algorithms and Optimization Problems - Searching with Partial Observations - Constraint Satisfaction Problems - Constraint Propagation - Backtracking Search - Game Playing - Optimal Decisions in Games - Alpha - Beta Pruning - Stochastic Games. Chapter-3 (KNOWLEDGE REPRESENTATION): First Order Predicate Logic - Prolog Programming - Unification - Forward Chaining - Backward Chaining - Resolution - Knowledge Representation - Ontological Engineering-Categories and Objects - Events - Mental Events and Mental Objects - Reasoning Systems for Categories - Reasoning with Default Information. Chapter-4 (SOFTWARE AGENTS): Architecture for Intelligent Agents - Agent communication - Negotiation and Bargaining - Argumentation among Agents - Trust and Reputation in Multi-agent systems. Chapter-5 (APPLICATIONS): Al applications - Language Models - Information Retrieval - Information Extraction - Natural Language Processing - Machine Translation - Speech Recognition - Robot -Hardware – Perception - Planning – Moving.

Want to learn about AI agents and assistants? Register for Virtual Agents Day here → https://ibm.biz/BdaAVa Want to play with the technology yourself? Explore our interactive demo → https://ibm.biz/BdKSer Join Jeff Crume as he dives into the distinctions between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Foundation Models and how these technologies have evolved over time. He also explores the latest advancements in Generative AI, including large language models, chatbots, and deepfakes - and clarifies common misconceptions, simplifies complex concepts, and discusses the impact these technologies have on various fields. AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdKSei

Making Friends with Machine Learning was an internal-only Google course specially created to inspire beginners and amuse experts. Today, it is available to everyone! This is the first hour-and-a-half of a six hour session. The course is designed to give you the tools you need for effective participation in machine learning for solving business problems and for being a good citizen in an increasingly AI-fueled world. MFML is perfect for all humans; it focuses on conceptual understanding (rather than the mathematical and programming details) and guides you through the ideas that form the basis of successful approaches to machine learning. It has something for everyone! Part 2 is available at http://bit.ly/mfml_part2 Part 3 is available at http://bit.ly/mfml_part3 To stay tuned for Part 4, don't forget to hit that that subscribe+notify button! Looking for hands-on ML/AI tutorials? Here are some of my favorite 10 minute walkthroughs: AutoML - https://console.cloud.google.com/?walkthrough_id=automl_quickstart Vertex AI - https://bit.ly/kozvertex AI notebooks - https://bit.ly/kozvertexnotebooks ML for tabular data - https://bit.ly/kozvertextables Text classification - https://bit.ly/kozvertextext Image classification - https://bit.ly/kozverteximage Video classification - https://bit.ly/kozvertexvideo

?Artificial Intelligence Engineer (IBM) - https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=ukzFI9rgwfU&utm_medium=DescriptionFirstFold&utm_source=Youtube ?IITK - Professional Certificate Course in Generative AI and Machine Learning (India Only) - https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=ukzFI9rgwfU&utm_medium=DescriptionFirstFold&utm_source=Youtube ?Purdue - Post Graduate Program in AI and Machine Learning - https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=ukzFI9rgwfU&utm_medium=DescriptionFirstFold&utm_source=Youtube ?IITG - Professional Certificate Program in Generative AI and Machine Learning (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=ukzFI9rgwfU&utm_medium=DescriptionFirstFold&utm_source=Youtube ?Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=ukzFI9rgwfU&utm_medium=DescriptionFirstFold&utm_source=Youtube This Machine Learning basics video will help you understand what Machine Learning is, what are the types of Machine Learning - supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into self-learning mode without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results. The below topics are explained in this Machine Learning basics video: 1. What is Machine Learning? ( 00:21 ) 2. Types of Machine Learning ( 02:43 ) 2. What is Supervised Learning? ( 02:53 ) 3. What is Unsupervised Learning? ( 03:46 ) 4. What is Reinforcement Learning? ( 04:37 ) 5. Machine Learning applications ( 06:25 ) Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning and follow the path toward your dream career- https://bit.ly/3eLuTUo Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy #MachineLearning #WhatIsMachineLearning #MachineLearningTutorial #MachineLearningBasics #MachineLearningTutorialForBeginners #Simplilearn ?? About Artificial Intelligence Engineer This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions. IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers. ? Key Features - Add the IBM Advantage to your Learning - 25 Industry-relevant Projects and Integrated labs - Immersive Learning Experience - Simplilearn's JobAssist helps you get noticed by top hiring companies ? Tools Covered - ChatGPT - Flask - Matplotlib - django - Python - Numpy - Pandas - SciPy - Keras - OpenCV - And Many More… ?Learn More at: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=MachineLearningscribe&utm_medium=DescriptionFirstFold&utm_source=youtube

?PGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executive-programs/pgp-generative-ai-machine-learning-certification-training ?Generative AI Course: Master's Program: https://www.edureka.co/masters-program/generative-ai-prompt-engineering-training This Edureka video on *Artificial Intelligence Full Course* will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples. The following topics are covered in this Artificial Intelligence Full Course: 00:00 Introduction to Artificial Intelligence Course 02:27 History Of AI 06:45 Demand For AI 08:46 What Is Artificial Intelligence? 09:50 AI Applications 16:49 Types Of AI 20:24 Programming Languages For AI 27:12 Introduction To Machine Learning 28:08 Need For Machine Learning 31:48 What Is Machine Learning? 34:13 Machine Learning Definitions 37:26 Machine Learning Process 49:13 Types Of Machine Learning 49:21 Supervised Learning 52:00 Unsupervised Learning 53:44 Reinforcement Learning 55:29 Supervised vs Unsupervised vs Reinforcement Learning 58:23 Types Of Problems Solved Using Machine Learning 1:04:49 Supervised Learning Algorithms 1:05:17 Linear Regression 1:11:20 Linear Regression Demo 1:26:36 Logistic Regression 1:35:36 Decision Tree 1:55:18 Random Forest 2:07:31 Naive Bayes 2:14:37 K Nearest Neighbour (KNN) 2:20:31 Support Vector Machine (SVM) 2:26:40 Demo (Classification Algorithms) 2:42:36 Unsupervised Learning Algorithms 2:42:45 K-means Clustering 2:50:49 Demo (Unsupervised Learning) 2:56:40 Reinforcement Learning 3:24:36 Demo (Reinforcement Learning) 3:31:41 AI vs Machine Learning vs Deep Learning 3:33:08 Limitations Of Machine Learning 3:36:32 Introduction To Deep Learning 3:38:36 How Deep Learning Works? 3:40:48 What Is Deep Learning? 3:41:50 Deep Learning Use Case 3:43:14 Single Layer Perceptron 3:50:56 Multi Layer Perceptron (ANN) 3:52:55 Backpropagation 3:54:39 Training A Neural Network 4:01:02 Limitations Of Feed Forward Network 4:03:18 Recurrent Neural Networks 4:05:36 Convolutional Neural Networks 4:09:00 Demo (Deep Learning) 4:29:02 Natural Language Processing 4:30:53 What Is Text Mining? 4:32:43 What Is NLP? 4:33:26 Applications Of NLP 4:35:53 Terminologies In NLP 4:41:19 NLP Demo 4:47:21 Machine Learning Masters Program ?? Check out the latest 2025 video on Top 10 Technologies for the most up-to-date insights! ? Top 10 Technologies to Learn in 2025 → https://youtu.be/5kjWh8lBxC4 ? ????? ???????? ???????????? ??? ????! ????????? ?? ??????? ??????? ???????: https://edrk.in/DKQQ4Py Python Full Course: https://www.youtube.com/watch?v=WGJJIrtnfpk Statistics and Probability Tutorial: https://www.youtube.com/watch?v=XcLO4f1i4Yo ? ??????? ?????? ????????? ? Python Programming Certification: http://bit.ly/37rEsnA ? Python Certification Training for Data Science: http://bit.ly/2Gj6fux ?. ??????? ??????? ??????? ? Data Scientist Masters Program: http://bit.ly/2t1snGM ? Machine Learning Engineer Masters Program: https://bit.ly/3Hi1sXN ? ??????? ?????????? ??????? ? Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh ? University of Cambridge Online Certifications: https://bit.ly/3RSNTXi Check out the entire Machine Learning Playlist: https://bit.ly/2NG9tK4 Check out the entire Machine Learning Blog list: https://bit.ly/2V2MnDW #edureka #artificialIntelligence #artificialIntelligenceTutorial #artificialIntelligenceFullCourse #artificialIntelligenceEngineer ?????????: https://t.me/edurekaupdates ????????: https://twitter.com/edurekain ?????????: https://www.linkedin.com/company/edureka ??????????: https://www.instagram.com/edureka_learning/ ?????????: https://www.facebook.com/edurekaIN/ ???????????: https://www.slideshare.net/EdurekaIN ????????: https://castbox.fm/networks/505?country=IN ???????: https://www.meetup.com/edureka/ ??????????: https://www.edureka.co/community/ ------------------------------------- About the Masters Program Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning. The Master's Program Covers Topics LIke: Python Programming PySpark HDFS Spark SQL Machine Learning Techniques and Artificial Intelligence Types Tokenization Named Entity Recognition Lemmatization Supervised Algorithms Unsupervised Algorithms Tensor Flow Deep learning Keras Neural Networks Bayesian and Markov’s Models Inference Decision Making Bandit Algorithms Bellman Equation Policy Gradient Methods. ------------- For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US & RoW: +1-8335643323 (toll-free)

This course from Harvard University explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like large language models, game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. This course has been updated for 2023 to include an in-depth section on large language models. ?? Course developed by Brian Yu for Harvard University. Learn more about Brian: https://brianyu.me/ ? Course resources: https://cs50.harvard.edu/ai/2020/ ?? Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba) ?? Course Contents ?? ?? (00:00:00) Introuction ?? (00:02:26) Search ?? (01:51:55) Knowledge ?? (03:39:39) Uncertainty ?? (05:34:08) Optimization ?? (07:18:52) Learning ?? (09:04:41) Neural Networks ?? (10:46:00) Language ? Thanks to our Champion and Sponsor supporters: ? davthecoder ? jedi-or-sith ? ???? ? Agustín Kussrow ? Nattira Maneerat ? Heather Wcislo ? Serhiy Kalinets ? Justin Hual ? Otis Morgan -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Dimensionality Reduction for Machine Learning and AI | Live Session | Applied AI Course #ml #ai #appliedaicourse ------------------------------------------------------- ------------------------------------------------------- ------------------------ The AppliedAICourse attempts to teach students/course-participants some of the core ideas in machine learning, data-science and AI that would help the participants go from a real world business problem to a first cut, working and deployable AI solution to the problem. Our primary focus is to help participants build real world AI solutions using the skills they learn in this course. This course will focus on practical knowledge more than mathematical or theoretical rigor. That doesn't mean that we would water down the content. We will try and balance the theory and practice while giving more preference to the practical and applied aspects of AI as the course name suggests. Through the course, we will work on 20+ case studies of real world AI problems and datasets to help students grasp the practical details of building AI solutions. For each idea/algorithm in AI, we would provide examples to provide the intuition and show how the idea to used in the real world. 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/appliedaicourse Soundcloud: https://soundcloud.com/applied-ai-course

For more information please visit https://www.appliedaicourse.com #ArtificialIntelligence,#MachineLearning,#DeepLearning,#DataScience,#NLP,#AI,#ML