129. The Oracle Groundbreakers Podcast is available via: Check the spelling of your keyword search. I explain in detail how it differs from TensorFlow 1.x, and how you can start using it on AWS: Deep Learning AMIs, Deep Learning Containers, and Amazon SageMaker.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources:* TensorFlow on AWS: https://aws.amazon.com/tensorflow* My SageMaker notebook: https://gitlab.com/juliensimon/dlnotebooks/tree/master/keras/07-keras-fmnist-tf20* A notebook giving you an overview of TensorFlow 2.0, by François Chollet, the creator of Keras: https://colab.research.google.com/drive/1UCJt8EYjlzCs1H1d1X0iDGYJsHKwu-NOThis podcast is also available in video: https://www.youtube.com/watch?v=Kqd7__Yllr0For more content, follow me at https://medium.com/@julsimon and at https://twitter.com/julsimon. Our three experts all have unique viewpoints. We suggest you try the following to help find what you’re looking for: Autonomous technologies such as artificial intelligence (AI) and machine learning (ML) are on the tip of every tongue in tech. “It’s about finding patterns in large amounts of data.” Helskyaho states, “ML is the heart, or the brain, of AI.” While Jarmul is more irreverent: “AI is what you call ML … Code included, of course!⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:* XGBoost built-in algo: https://gitlab.com/juliensimon/ent321* XGBoost built-in framework: https://gitlab.com/juliensimon/dlnotebooks/-/blob/master/sagemaker/09-XGBoost-script-mode.ipynb * BYO with Scikit-learn: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb * Deploying XGBoost with mlflow: https://youtu.be/jpZSp9O8_ew * New model format: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html* Converting pickled models: https://github.com/dmlc/xgboost/blob/master/doc/python/convert_090to100.py This podcast is also available in video at https://youtu.be/w0F4z0dMdzI.For more content, follow me on:* Medium https://medium.com/@julsimon* Twitter https://twitter.com/@julsimon, In this episode, I cover new features on Amazon Personalize (recommendation & personalization), Amazon Polly (text to speech), and Apache MXNet (Deep Learning). I demo real-time profanity filtering with Transcribe (run for cover), and Elastic Inference with TensorFlow and SageMaker.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon, In this episode, I go through our latest announcements on AWS Amazon Augmented AI, Amazon SageMaker Studio, Amazon Sagemaker, and PyTorch.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️AWS blog posts mentioned in the podcast:* https://aws.amazon.com/blogs/machine-learning/announcing-availability-of-inf1-instances-in-amazon-sagemaker-for-high-performance-and-cost-effective-machine-learning-inference/* https://aws.amazon.com/blogs/aws/announcing-torchserve-an-open-source-model-server-for-pytorch/ For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon, In this episode, I go through our latest announcements on AWS Textract, Amazon Polly. 126), Remove noise from data with deep learning (Ep.125), What is contrastive learning and why it is so powerful? “AI and ML are just applied math,” says Berger. But what is the difference between AI and ML? Berger, Helskyaho, and Jarmul explain what makes AI and ML solutions powerful as well as the challenges we face from them. 130, Art(ificial) Intelligence: Pindar Van Arman Builds Robots that Paint - Ep. As she spends her time working on customer projects, we talk about ML in the trenches: framing problems, building datasets, picking algos, deploying to production, and more.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️This podcast is also available in video at https://youtu.be/74LwQP9oKU4For more content, follow me on:- Medium: https://medium.com/@julsimon- Twitter: https://twitter.com/julsimon, In this episode, I have a chat with Francesco Pochetti, a Data Scientist who worked on Amazon Kindle for 4 years. If you're beginning with the field, this should save you quite a bit of frustration! AI/ML & Big Data Podcasts. Connect: @HeliFromFinland, linkedin.com/in/helihelskyaho/, Senior Director of Product Management for Machine Learning, AI, and Cognitive Analytics, Oracle I show you how to create an index, add data sources, and then I run queries using the AWS console and the AWS CLI.

.

Pomona Goddess Statue, Madonna Of The Chair Analysis, Plain Hamburger Calories, Kale Quinoa Salad Vegan, As Seen On Tv Non Stick Pan, Keto Marinade For Pork Chops, The Hen Who Dreamed She Could Fly Review, Gospel Church Logo,