It’s time to reveal the magician’s secrets behind deploying machine learning models! In this tutorial, I go through an example machine learning deployment scenario using Google Cloud and an image recognition app called Food Vision πŸ”πŸ‘. Get all the code on GitHub – https://github.com/mrdbourke/cs329s-ml-deployment-tutorial Slides – https://github.com/mrdbourke/cs329s-ml-deployment-tutorial/blob/main/CS329s-deploying-ml-models-tutorial.pdf Full CS329s syllabus – https://stanford-cs329s.github.io/index.html Learn ML (my beginner-friendly ML course) – https://dbourke.link/mlcourse Connect elsewhere: Web – https://www.mrdbourke.com Get email updates on my work – https://www.mrdbourke.com/newsletter Timestamps: 0:00 – Intro/hello 1:42 – Presentation start (what we’re going to cover) 6:00 – Food Vision πŸ”πŸ‘ (the app we’re building) recipe 11:16 – The end goal we’re working towards (data flywheel) 13:07 – The data flywheel: the holy grail of ML apps 14:57 – Tesla’s data flywheel 17:02 – Food Vision’s data flywheel 18:24 – Deploying a model on the cloud outline 21:14 – Steps we’re going to go through to deploy our app 27:06 – Question: β€œHow do you identify hard samples in your data?” 37:53 – Creating a bucket on Google Storage 45:51 – Uploading to Google Storage from Google Colab 48:02 – Deploying a model to AI Platform 52:50 – Creating an AI Platform Prediction version 58:10 – Creating a Service Account to access our model on Google Cloud 1:02:32 – Authenticating our app with our private Service Account key 1:09:19 – What happens when we run make gcloud-deploy 1:11:27 – Problems you’ll run into when deploying your models 1:20:12 – Extensions you could perform on this tutorial 1:20:49 – Part 2 [More]
I had so many requests for how to do this from my 2013 video. I finally threw together an example project. This is a quick and dirty Jarvis application. If you’ve ever seen any of the Iron Man movies you will know what this is. This is a C# application using the .NET framework. Have fun using the code and share what you create with it. Happy coding! Code Project By Sperneder Patrick: http://www.codeproject.com/Articles/380027/Csharp-Speech-to-Text My other Jarvis Video (I’m going to move it to this channel): https://www.youtube.com/watch?v=JU0Hu5YFzro&list=UUWoJq7OQwglzAnb-23kcopQ Here is the download link for the C# source: https://drive.google.com/file/d/0Bw_USLQ_AgNuQk11S0ZxTkJOeEE/view?usp=sharing
Android has an inbuilt feature speech to text through which you can provide speech input to your app. With this feature you can add some of the cool features to your app like adding voice navigation and it is very helpful when you are targeting disabled people. In the background how voice input works is, the speech input will be streamed to a server, on the server voice will be converted to text and finally text will be sent back to our app. Other tutorials : 1) Create a custom AVD :https://youtu.be/Cg7BVTk6r5E 2) Basic Android App :http://youtu.be/q98NC73LEgI 3) Calculator App :https://youtu.be/mrjOLG2Grt0 4) How to create a new activity :https://youtu.be/-xljI2_TRZg 5) How to create a login form :https://youtu.be/x6jQAaLz1O8 Find me here : Tumblr : https://www.tumblr.com/blog/priyanka0304 Google+ : https://plus.google.com/u/0/b/105970252005982916681/105970252005982916681/posts Twitter : https://twitter.com/AndroidAcademy1 Facebook : https://www.facebook.com/AndroidAcademy8?ref=hl
πŸ™‹β€β™‚οΈ We’re launching an exclusive part-time career-oriented certification program called the Zero to Data Science Bootcamp with a limited batch of participants. Learn more and enroll here: https://www.jovian.ai/zero-to-data-science-bootcamp πŸ”— Resources used β€’ Notebook created in the workshop: https://jovian.ai/aakashns-6l3/deep-learning-project-live β€’ Guidelines and datasets for deep learning projects: https://jovian.ai/learn/deep-learning-with-pytorch-zero-to-gans/assignment/course-project πŸ’» In this live hands-on workshop, we’ll build a deep learning project from scratch in 2.5 – 3 hours. You can follow along to build your own project. Take our Free Certification Course β€œDeep Learning with PyTorch: Zero to GANs” to learn the required skills: http://zerotogans.com Here’s an outline of the workshop: πŸ“„ Find an interesting unstructured dataset online (images, text, audio, etc.) ❓ Identify the type of problem: regression, classification, generative modeling, etc. πŸ€” Identify the type of neural network you need: fully connected, convolutional, recurrent, etc. πŸ›  Prepare the dataset for training (set up batches, apply augmentations & transforms) πŸ”ƒ Define a network architecture and set up a training loop ⚑ Train the model and evaluate its performance using a validation/test set πŸ§ͺ Experiment with different network architectures, hyperparameters & regularization techniques πŸ“° Document and publish your work in a Jupyter notebook or blog post πŸ“’ Datasets from the workshop: Chest X-Ray Images (Pneumonia) – https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia Fruits 360 – https://www.kaggle.com/moltean/fruits Flowers Recognition – https://www.kaggle.com/alxmamaev/flowers-recognition Malaria Cell Images Dataset – https://www.kaggle.com/iarunava/cell-images-for-detecting-malaria Intel Image Classification – https://www.kaggle.com/puneet6060/intel-image-classification Best Artworks of All Time – https://www.kaggle.com/ikarus777/best-artworks-of-all-time CelebFaces Attributes (CelebA) Dataset – https://www.kaggle.com/jessicali9530/celeba-dataset Open Datasets – https://github.com/JovianML/opendatasets βš™ Check out these projects for inspiration: β€’ Blindness [More]
Create Free Tier Account: https://aws.amazon.com/free/?all-free-tier.sort-by=item.additionalFields.SortRank&all-free-tier.sort-order=asc Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici Discord Server Link: https://discord.gg/tvAJuuy Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw 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 Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
In this video, make sure you define the X’s like so. I flipped the last two lines by mistake: X = np.array(df.drop([‘label’],1)) X = preprocessing.scale(X) X_lately = X[-forecast_out:] X = X[:-forecast_out:] To forecast out, we need some data. We decided that we’re forecasting out 10% of the data, thus we will want to, or at least *can* generate forecasts for each of the final 10% of the dataset. So when can we do this? When would we identify that data? We could call it now, but consider the data we’re trying to forecast is not scaled like the training data was. Okay, so then what? Do we just do preprocessing.scale() against the last 10%? The scale method scales based on all of the known data that is fed into it. Ideally, you would scale both the training, testing, AND forecast/predicting data all together. Is this always possible or reasonable? No. If you can do it, you should, however. In our case, right now, we can do it. Our data is small enough and the processing time is low enough, so we’ll preprocess and scale the data all at once. In many cases, you wont be able to do this. Imagine if you were using gigabytes of data to train a classifier. It may take days to train your classifier, you wouldn’t want to be doing this every…single…time you wanted to make a prediction. Thus, you may need to either NOT scale anything, or you may scale the data separately. As [More]
Do you want to become a 6-figure developer with Python? Check out the best Python course on the planet πŸ‘‰ 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 πŸ‘‰ https://discord.gg/7nazyQUSNe Time Stamps πŸ‘‡ … ENJOYπŸ”₯ 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
( TensorFlow Training – https://www.edureka.co/ai-deep-learning-with-tensorflow ) This Edureka “Neural Network Tutorial” video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail. Below are the topics covered in this tutorial: 1. Why Neural Networks? 2. Motivation Behind Neural Networks 3. What is Neural Network? 4. Single Layer Percpetron 5. Multi Layer Perceptron 6. Use-Case 7. Applications of Neural Networks Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai Post Graduate Certification in Data Science with IIT Guwahati – https://www.edureka.co/post-graduate/data-science-program (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) – – – – – – – – – – – – – – How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 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 have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! – – – – – – – – – – – – – – About the Course Edureka’s Deep learning with [More]
πŸ”₯ 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 βœ…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! πŸ”₯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 βœ…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]
πŸ”₯ Enroll for FREE Machine Learning Course & Get your Completion Certificate: https://www.simplilearn.com/learn-machine-learning-basics-skillup?utm_campaign=MachineLearning&utm_medium=Description&utm_source=youtube This Machine Learning tutorial will help you understand why Machine Learning came into the picture, what is Machine Learning, and the types of Machine Learning., Machine Learning algorithms with a detailed explanation on linear regression, decision tree & support vector machine, and at the end you will also see a use case implementation where we classify whether a recipe is of a cupcake or muffin using SVM algorithm. Dataset Link – https://drive.google.com/drive/folders/1W7kaFk2vUkwEfvFwuLyJpMX5-ZH7uPyy Machine Learning Tutorial Part – 2: https://www.youtube.com/watch?v=_Wkx_447zBM Below topics are explained in this Machine Learning tutorial: 00:00 – 00:45 Why Machine Learning? 00:45 – 04:52 What is Machine Learning? 04:52 – 11:34 Types of Machine Learning 11:34 – 16:41 Machine Learning Algorithms 16:41 – 25:43 Linear Regression 25:43 – 34:00 Decision Trees 34:00 – 36:02 Support Vector Machine 36:02 – 01:02:40 Use case: Classify whether a recipe is of a cupcake or a muffin using SVM 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 towards your dream career- https://bit.ly/2VTB8Nc You can also go through the Slides here: https://goo.gl/m5Txob Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy #MachineLearning #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse #Simplilearn What is Machine Learning? Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to [More]
Learn more advanced front-end and full-stack development at: https://www.fullstackacademy.com FastText is an open-source, Natural Processing Language (NLP) library created by Facebook AI Research that allows users to efficiently learn word representations and sentence classification. In this FastText Tutorial, we discuss how FastText enables text classification through supervised learning. Watch this video to learn: – How text classification models are built and evaluated using FastText – Tricks used in FastText that improve the time complexity of model building – How FastText can be used to identify spam in a sample inbox
In this video, I have created an AI desktop virtual assistant using python along with several related techniques to write effective python programs. This video is a part of my python for absolute beginners playlist – https://www.youtube.com/playlist?list=PLK8cqdr55Tss0puRoHDBagvj7Qjin9axl
** RPA Training: https://www.edureka.co/robotic-process-automation-training ** This session on RPA Blue Prism will cover all the basic concepts of the RPA Tool Blue Prism. Following are the topics covered in the video: What is Robotic process Automation? RPA Tools What is Blue Prism? Features of Blue Prism Blue Prism Components Benefits of Blue prism Case Study of Blue Prism Companies Using Blue Prism RPA Playlist: https://bit.ly/2B53HLe RPA Blog Series: https://bit.ly/2Ay1bzG Subscribe to our Edureka YouTube channel to get video updates: https://goo.gl/6ohpTV 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 How does it work? 1. This is a 4 Week Instructor-led Online Course, 25 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 have to work on a project, based on which we will provide you a Grade and a Verifiable Certificate! ————————————————————————————– About the Robotic Process Automation Course Edureka’s RPA training helps you to understand the concepts around Robotic Process Automation using the leading RPA tool named β€˜UiPath’. Robotic Process Automation is the automation of repetitive and rules-based human tasks working with the software applications at the presentation/UI level i.e. no software integrations are needed at middleware, server or database levels. In this course, you will learn about the RPA concepts and will gain in-depth knowledge on UiPath tool using which you will be able [More]
Text to speech (Speak) in Microsoft word 2016 – How to enable.. That’s the video all about.. Text to speech option or popularly called as voice recognition or speak was an Option that is used to read text inside the document in Microsoft Word 2016.. If you wish to enable the text to speech then just follow the steps shown in the above video.. Comment if you have any doubts.. Thanks for watching.
Learn Artificial Intelligence from leading experts and attain a Dual Certificate in AI and Machine Learning from world-renowned universities. Take the step towards your professional growth by obtaining expertise in the real-world application of the latest technological tools of AI. Over 500+ Hiring Partners & 8000+ career transitions over varied domains. Know More: https://glacad.me/3qSjmt0 For data sets, code files and projects associated with course please enroll for free at: https://www.greatlearning.in/academy/learn-for-free/courses/machine-learning-with-python Machine learning is changing the world that we live in. Top companies such as Facebook, Google, Microsoft and Amazon are looking for machine learning engineers and the average salary of a machine learning engineer is around 120k$ dollars. Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science, Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. https://glacad.me/3uBbddU Get the free Great Learning App for a seamless experience, enroll for free courses and watch them offline by downloading them. https://glacad.me/3cSKlNl This full course on Machine Learning with Python will be taught by Dr Abhinanda Sarkar. Dr Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. He is ranked amongst the Top 3 Most Prominent Analytics & Data Science Academicians in India. He has taught applied mathematics at the Massachusetts Institute of Technology (MIT) as well as been visiting [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 ⭐️ πŸ“• Module 2: Introduction to TensorFlow – https://colab.research.google.com/drive/1F_EWVKa8rbMXi3_fG0w7AtcscFq7Hi7B#forceEdit=true&sandboxMode=true πŸ“— Module 3: Core Learning Algorithms – https://colab.research.google.com/drive/15Cyy2H7nT40sGR7TBN5wBvgTd57mVKay#forceEdit=true&sandboxMode=true πŸ“˜ Module 4: Neural Networks with TensorFlow – https://colab.research.google.com/drive/1m2cg3D1x3j5vrFc-Cu0gMvc48gWyCOuG#forceEdit=true&sandboxMode=true πŸ“™ Module 5: Deep Computer Vision – https://colab.research.google.com/drive/1ZZXnCjFEOkp_KdNcNabd14yok0BAIuwS#forceEdit=true&sandboxMode=true πŸ“” Module 6: Natural Language Processing with RNNs – https://colab.research.google.com/drive/1ysEKrw_LE2jMndo1snrZUh5w87LQsCxk#forceEdit=true&sandboxMode=true πŸ“’ 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]
This tutorial was recorded at KDD 2020 as a live, hands-on tutorial. The content is available at https://dssg.github.io/fairness_tutorial/
Text summarization is the process of creating a short, accurate, and fluent summary of a longer text document. It is the process of distilling the most important information from a source text. Automatic text summarization is a common problem in machine learning and natural language processing (NLP). Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover relevant information and to consume relevant information faster. πŸ”Š Watch till last for a detailed description 01:21 What is text summarization? 05:19 Installing the packages 15:10 Sentence tokenization πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡ βœοΈπŸ†πŸ…πŸŽπŸŽŠπŸŽ‰βœŒοΈπŸ‘Œβ­β­β­β­β­ ENROLL in My Highest Rated Udemy Courses to πŸ”‘ Unlock Data Science Interviews πŸ”Ž and Tests πŸ“š πŸ“— 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 πŸ“Š πŸ“ˆ 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 πŸ“˜ πŸ“™ Natural Language Processing (NLP) in Python for Beginners NLP: Complete Text Processing with Spacy, NLTK, Scikit-Learn, Deep Learning, word2vec, GloVe, BERT, RoBERTa, DistilBERT Course Link: https://bit.ly/intro_nlp . πŸ“ˆ πŸ“˜ 2021 Python for Linear Regression in Machine Learning Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal. You will learn how to build a Linear Regression model from scratch. Course Link: https://bit.ly/regression-python πŸ“™πŸ“Š 2021 R 4.0 Programming [More]
πŸ”΅Edureka Python Programming Certification Course (Use Code “π˜πŽπ”π“π”ππ„πŸπŸŽ”): 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]
This half hour tutorial takes you step by step through the fundamental concepts you need to know to build a no code chatbot with Power Virtual Agents. Watch and pause and build your own bot side by side with this step-by-step instructional video. You will learn: – How to create a bot – What topics are and how to create them – How to use variables to store information from the user response for the bot to use later – What entity extraction is and how it enables the bot to have a natural conversation, including skipping questions – How to test your bot, and publish it to a demo website to share with others – How to use Power Automate to call an action – in this example we post information from a bot chat into Microsoft Teams – How to use the topic redirect feature
An updated guide on large ME controllers and P2P networking. You can support me and the channel! Read more here: https://www.patreon.com/tkh I have done videos about these things before, but when I got a question to help out with a problem I took the opportunity to also make an updated video on the subject. I think the old videos didn’t have the visible channel info from The One Probe or the colored tunnels which makes things much easier compared to how it used to be. Btw, I think it’s called “Back bone network”… πŸ˜‰ Read more about me and what I do here: http://tkh.one/ All my AE2 videos are gathered in this playlist: https://www.youtube.com/playlist?list=PLPCqiTnvx2Gv3rd5fpVPpKtb2oH53eYYa Key items and blocks in this video: – ME Controller – P2P Tunnel – Memory Card – ME Networks – Auto-crafting If you like what you see, please hit “like” and feel free to comment and share. And of course, subscribe if you want to see more! I can be found on social medias as well, for video announcements and general updates. They are also the preferred way to send a non-video related question or comment. Oh, and sometimes I do things on Twitch as well! http://twitter.com/therealtkh https://www.facebook.com/therealtkh http://www.twitch.tv/therealtkh/ Game details for this video: Twitch App Minecraft 1.12.2 – Custom Pack Forge 14.23.5.2814 Applied Energistics 2 [rv6-stable-6] Find Applied Energistics 2 here: http://ae-mod.info/
This video contains python implementation of Realtime Face Emotion Recognition 1) Brainstorming (background of facial emotion recognition) (i)Challenges in FER 2013 dataset 2) OpenCV for drawing rectangles and overlaying text data 3) Face emotion recognition using DeepFace library 4) Live Video demo using OpenCV + DeepFace for Webcam
Deep learning, Deepfake, Machine Learning, Classification algorithm, Regression Algorithm, Supervised ML, Clustering Algorithm,Business Intelligence (BI),Data Engineering,Decision Science,Artificial Intelligence (AI),Machine Learning,Supervised Learning,Classification,Clustering,Deep Learning,Linear Regression,A/B Testing,Hypothesis Testing,Statistical Power,Statistical Power,Standard Error,Exploratory Data Analysis (EDA),Data Visualization,R, Python, SQL, GitHub, ETL, Data Models,
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