🔥 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]
Learn more: http://oracle.com/analytics Discover what Oracle augmented analytics is and how it helps businesses analyze all their data for better decisions.
Sagar Patel, Ana Arriola, Saschka Unseld and Jamie Myrold chime in on AR, VR, and AI in this panel discussion that took place at San Francisco Design Week.
Recorded on Mar 24 2016 at GCP NEXT 2016 in San Francisco. Visual effects rendering is a computationally intensive process where one second of screen-time can require thousands of cores and terabytes of frame data. Learn how Academy Award-winning and recognized studios take advantage of cloud economics and Google’s on-demand computing to realize their creative visions and expand this digital medium for storytelling. Speakers: Julia Ferraioli, Google & David Zuckerman, Wix
In the video: 10. Blockchain and Analytics in the Cloud | Tech2Teach Blockchain is a secure, distributed, open technology that can help speed up processes, lower costs, and build transparency and traceability in transactional applications. It is an immutable Network allowing members to view only those transactions that are relevant to them. The more open, diverse, and distributed the network, the stronger the trust and transparency in the data and transactions. 85% of businesses today rely on multiple clouds to meet their IT needs, with more than 70% using more than three. These businesses need to be able to move applications and data across multiple clouds easily and securely, leading to the emerging demand to build and manage business applications such as blockchain for the multi cloud environment. Blockchain and AI, much like IoT and AI, powered by the cloud, also have a three-way relationship. Other videos related to it on You Tube: Data Driven #5: Blockchain and Big Data Lecture 54: Blockchain for Data Analytics – I (Blockchain for Big Data) Understanding blockchain analytics How does a blockchain work – Simply Explained The Convergence of Blockchain, Machine Learning, and the Cloud | Steve Lund | TEDxBYU Blockchain & Internet of Things Blockchain and Analytics Blockchain for Big Data, Storage and Analytics Blockchain and Google: How Blockchain Technology Will Impact Google #Blockchain​ #Technology​ #Coding #bigdata #Blockchain​ + #OracleAnalytics​ ! A presentation by #Analytics​ #Rockstar​ Gary Crisci that you’re not going to want to miss! Here is a quick preview. Register [More]
Cloud Tensor Processing Units (TPUs ) enable machine learning engineers and researchers to accelerate TensorFlow workloads with Google-designed supercomputers on Google Cloud Platform. This talk will include the latest Cloud TPU performance numbers and survey the many different ways you can use a Cloud TPU today – for image classification, object detection, machine translation, language modeling, sentiment analysis, speech recognition, and more. You’ll also get a sneak peak at the road ahead. Rate this session by signing-in on the I/O website here → https://goo.gl/5HcnkN Watch more GCP sessions from I/O ’18 here → https://goo.gl/qw2mR1 See all the sessions from Google I/O ’18 here → https://goo.gl/q1Tr8x Subscribe to the Google Cloud Platform channel → https://goo.gl/S0AS51 #io18 #GoogleIO #GoogleIO2018
In this video, Yufeng Guo applies deep learning models to local prediction on mobile devices. Yufeng shows you how to use TensorFlow to implement a machine learning model that is tailored to a custom dataset. You will come away knowing enough to get started solving your own deep learning problems. Missed the conference? Watch all the talks here: https://goo.gl/c1Vs3h Watch more talks about Big Data & Machine Learning here: https://goo.gl/OcqI9k
Deployment Videos Link :https://www.youtube.com/watch?v=bjsJOl8gz5k&list=PLZoTAELRMXVOAvUbePX1lTdxQR8EY35Z1 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
Watch the newest video from Big Think: https://bigth.ink/NewVideo Join Big Think Edge for exclusive videos: https://bigth.ink/Edge ———————————————————————————- ———————————————————————————- ABOUT BIG THINK: Smarter Faster™ Big Think is the leading source of expert-driven, actionable, educational content — with thousands of videos, featuring experts ranging from Bill Clinton to Bill Nye, we help you get smarter, faster. S​ubscribe to learn from top minds like these daily. Get actionable lessons from the world’s greatest thinkers & doers. Our experts are either disrupting or leading their respective fields. ​We aim to help you explore the big ideas and core skills that define knowledge in the 21st century, so you can apply them to the questions and challenges in your own life. Other Frequent contributors include Michio Kaku & Neil DeGrasse Tyson. Michio Kaku Playlist: https://bigth.ink/kaku Bill Nye Playlist: https://bigth.ink/BillNye Neil DeGrasse Tyson Playlist: https://bigth.ink/deGrasseTyson Read more at Bigthink.com for a multitude of articles just as informative and satisfying as our videos. New articles posted daily on a range of intellectual topics. Join Big Think Edge, to gain access to a world-class learning platform focused on building the soft skills essential to 21st century success. It features insight from many of the most celebrated and intelligent individuals in the world today. Topics on the platform are focused on: emotional intelligence, digital fluency, health and wellness, critical thinking, creativity, communication, career development, lifelong learning, management, problem solving & self-motivation. BIG THINK EDGE: https://bigth.ink/Edge If you’re interested in licensing this or any other Big Think clip for commercial [More]
Fei-Fei Li came to the U.S. from China at 16 with a love for science and she never looked back. Educated at Princeton and Caltech, her early work in robotics revolutionized machine learning and AI. Her focus on inclusion in tech careers and diversity in what we teach machines suggests that tomorrow’s robots won’t be sexist.
Fei-Fei Li came to the U.S. from China at 16 with a love for science and she never looked back. Educated at Princeton and Caltech, her early work in robotics revolutionized machine learning and AI. Her focus on inclusion in tech careers and diversity in what we teach machines suggests that tomorrow’s robots won’t be sexist. makers.com/techmakers
github url :https://github.com/krishnaik06/Google-Cloud-Platform-Deployment 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
Discover how CSP enables you to modernize your applications no matter where they are. Plus, learn how to undo human bias at scale with KubeFlow. Watch more: Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform
Welcome to part 4 of the Google Cloud tutorial series. In this part, we’re going to explore some of the Natural Language API. We’re going to focus on the entity recognition and sentiment analysis, but you can also do syntactical analysis with this API. As usual, you will need to both enable this API and of course have the API credentials setup as we did in Part 2. From here, things should begin to look familiar with the APIs, for example we’ll have client = language.Client(), and then we’ll get all sorts of methods that we can do with some input, which, in this case, will be text. Sample code: https://pythonprogramming.net/natural-language-api-google-cloud-tutorial/ https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Hello All, In this video we will be discussing about the differences Between Infrastructure as a Service and Platform as a Service cloud platforms Support me in Patreon: https://www.patreon.com/join/2340909? You can buy my book on Finance with Machine Learning and Deep Learning from the below url amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=ac229c9a45954acc19c1b2fa2ca96e23&creativeASIN=1789346371 Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below amazon url: https://www.amazon.in/Hands-Machine-Learning-Scikit-Learn-Tensor/dp/9352135210/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=a706a13cecffd115aef76f33a760e197&creativeASIN=9352135210 Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06 Subscribe my unboxing Channel https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning! Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K- You can buy my book on Finance with Machine Learning and Deep Learning from the below url amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 THINGS to support my channel LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL
New advances in machine learning are helping organizations optimize operations, maximize output, and automate manual processes. However, the scalability of such solutions across hundreds or thousands of unique assets is extremely difficult and requires teams of data scientists and technicians to constantly build, test, and deploy machine learning models. What if you could automatically create customized machine learning models? In this session, we will discuss how Darwin™, SparkCognition’s automated model building platform, solves these problems for Apergy by automating machine learning model development. We will also offer a window into how Darwin™ empowers upstream oil and gas, as well as other industries, to improve business operations with the assistance of Google’s powerful Cloud Platform. MLAI109 Event schedule → http://g.co/next18 Watch more Machine Learning & AI sessions here → http://bit.ly/2zGKfcg Next ‘18 All Sessions playlist → http://bit.ly/Allsessions Subscribe to the Google Cloud channel! → http://bit.ly/NextSub
Machine learning is notorious for reinforcing existing bias, but it can also be used to counteract it. Primer developed an ML system called Quicksilver that identifies and describes notable women of science who are missing from Wikipedia. It takes millions of news documents as input and generates first-draft biographical articles. Kubeflow made it far easier to scale and maintain this system. Come learn how Primer partnered with Google to migrate to GCP in order to: * Deploy the same code to multiple physical environments * Affordably scale an existing ML app using Kubeflow with auto-provisioning * Continuously train hundreds of thousands of models using Kubeflow pipelines Watch more: Next ’19 ML & AI Sessions here → https://bit.ly/Next19MLandAI Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform Speaker(s): John Bohannon, Michelle Casbon Session ID: MLAI206 product:Compute Engine;
Machine learning is notorious for reinforcing existing bias, but it can also be used to counteract it. Primer developed an ML system called Quicksilver that identifies and describes notable women of science who are missing from Wikipedia. It takes millions of news documents as input and generates first-draft biographical articles. Kubeflow made it far easier to scale and maintain this system. Come learn how Primer partnered with Google to migrate to GCP in order to: * Deploy the same code to multiple physical environments * Affordably scale an existing ML app using Kubeflow with auto-provisioning * Continuously train hundreds of thousands of models using Kubeflow pipelines Watch more: Next ’19 ML & AI Sessions here → https://bit.ly/Next19MLandAI Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform Speaker(s): John Bohannon, Michelle Casbon Session ID: MLAI206 product:Compute Engine;
Al Burgio & Matthew Roszak, sit down for a fireside chat with John Furrier for Global Cloud & Blockchain Summit 2018 from The Westin Harbour Castle in Toronto, Ontario.
Today data scientist is turning to cloud for AI and HPC workloads. However, AI/HPC applications require high computational throughput where generic cloud resources would not suffice. There is a strong demand for OpenStack to support hardware accelerated devices in a dynamic model. In this session, we will introduce OpenStack Acceleration Service – Cyborg, which provides a management framework for accelerator devices (e.g. FPGA, GPU, NVMe SSD). We will also discuss Rack Scale Design (RSD)
Learn how to build and deploy a machine learning model to Cloud ML Engine, then make it available to the world via Firebase Cloud Functions. https://angularfirebase.com/lessons/serverless-machine-learning-with-python-and-firebase-cloud-functions/ – Radi Cho’s TensorFlow Repo https://github.com/radi-cho/tfjs-firebase – ML Engine https://cloud.google.com/ml-engine/ – Datalab https://cloud.google.com/datalab/
Let’s discuss whether you should train your models locally or in the cloud. I’ll go through several dedicated GPU options, then compare three cloud options; AWS, Google Cloud, and FloydHub. I was not endorsed by anyone for this. Code for this video: https://github.com/floydhub/fast-style-transfer Please Subscribe! And like. And comment. That’s what keeps me going. High Budget GPU: Titan XP https://www.amazon.com/NVIDIA-GeForce-Pascal-GDDR5X-900-1G611-2500-000/dp/B01JLKP3IS Medium Budget GPU: https://www.amazon.com/MSI-GAMING-GTX-1060-6G/dp/B01IEKYD5U Small Budget GPU: https://www.amazon.com/dp/B01MF7EQJZ Build a Deep Learning machine: https://medium.com/@ncondo/build-a-deep-learning-rig-for-800-4434e21a424f https://medium.com/towards-data-science/building-your-own-deep-learning-box-47b918aea1eb https://www.oreilly.com/learning/build-a-super-fast-deep-learning-machine-for-under-1000 More learning resources: http://www.infoworld.com/article/3179785/cloud-computing/aws-vs-azure-vs-google-cloud-which-free-tier-is-best.html https://thehftguy.com/2016/06/15/gce-vs-aws-in-2016-why-you-should-never-use-amazon/ https://medium.com/@davidmytton/aws-vs-google-cloud-flexibility-vs-operational-simplicity-dca4324b03d4 https://news.ycombinator.com/item?id=13659914 Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
SUBSCRIBE: https://www.youtube.com/user/StartupGrind STARTUP GRIND: https://www.startupgrind.com/ GLOBAL CONFERENCE: https://www.startupgrind.com/conference/ Mike Abbott, Partner of Kleiner Perkins Caufield & Byers, sits with Dr. Fei Fei Li, Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab. Dr Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She has published more than 150 scientific articles in top-tier journals and conferences and invented ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. As of January 2017, Fei-Fei Li is spending her sabbatical at Google Cloud as Chief Scientist AI/ML. EUROPE CONFERENCE: https://www.startupgrind.com/europe/ TWITTER: https://twitter.com/StartupGrind FACEBOOK: https://www.facebook.com/StartupGrind/ INSTAGRAM: https://www.instagram.com/startup/
Hear from Diane Greene, SVP of Google Cloud; Sundar Pichai, CEO of Google; Eric Schmidt, Chairman of Alphabet and Fei-Fei Li, Chief Scientist for Google Cloud Machine Learning and AI and Professor of Computer Science at Stanford. Our lineup of executives will discuss what Google Cloud offers today and discuss Google Cloud’s vision for the future. Attendees will also hear how our customers and partners are embracing the cloud in new and innovative ways. Missed the conference? Watch all the talks here: https://goo.gl/c1Vs3h
There are revolutionary changes happening in hardware and software that are democratizing machine learning (ML). Whether you’re new to ML or already an expert, Google Cloud Platform has a variety of tools for users. This session will start with the basics: using a pre-trained ML model with a single API call. It’ll then look at building and training custom models with TensorFlow and Cloud ML Engine, and will end with a demo of AutoML Vision – a new tool for training a custom image classification model without writing model code. Rate this session by signing-in on the I/O website here → https://goo.gl/4n5aYA Watch more GCP sessions from I/O ’18 here → https://goo.gl/qw2mR1 See all the sessions from Google I/O ’18 here → https://goo.gl/q1Tr8x Subscribe to the Google Cloud Platform channel → https://goo.gl/S0AS51 #io18