Pragmatic AI Labs

Pragmatic AI Labs

Views:
590,305
Subscribers:
17,700
Videos:
1,146
Duration:
19:22:43:52
United States
United States

Pragmatic AI Labs is an American YouTube channel which has at least 17.7 thousand subscribers, publishing roughly 1.15 thousand videos which altogether total approximately 590.31 thousand views.

Created on ● Channel Link: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q



All Videos by Pragmatic AI Labs



PublishedVideo TitleDurationViewsCategoryGame
2020-11-27A walkthrough of Azure ML Studio Designer5:43428Walkthrough
2020-11-26How to create effective technical demo videos1:34359Guide
2020-11-25Building a simple HTML website with AWS Lambda5:384,194
2020-11-24Learn to configure Azure Machine Learning Workspaces3:022,263
2020-11-19What is Testing?4:59164
2020-11-18Learn how to perform auto hyperparameter tuning in Azure3:26147Guide
2020-11-12DevOps Best Practices3:36164
2020-11-12Flask Elastic Beanstalk12:28996
2020-11-11Benefits of DevOps3:12517
2020-11-09Use Trello for project management4:24146
2020-11-09Create an Apache Web Service with EC2 Spot9:59171
2020-11-04Introduction to Github Actions7:59282
2020-11-04Construct a Python Project Scaffold18:573,127
2020-11-01What is Continuous Integration?3:5892
2020-11-01What is AWS Cloud9?9:2114,660
2020-11-01How do I setup Github Actions?9:2697
2020-10-30How to profile data with Azure ML Studio1:33458
2020-10-27Python Functions: Inputs, Unit of Work, Return1:33:35410
2020-10-27Effective Technical Teamwork5:57124
2020-10-27Project Management Anti-Patterns4:53300
2020-10-25How Can You Create Effective Technical Discussions10:42902Discussion
2020-10-25Learning Serverless1:23:00146
2020-10-21Machine Learning Model Edge Cases2:05159
2020-10-17Building Cloud ETL Pipelines1:12:01854
2020-10-15Github Action Tricks and Tips for Many Clouds1:28:051,866
2020-10-13YAGNI: Catching up with Matt & Noah55:5938
2020-10-13How to perform model interpretation in Azure3:2431Guide
2020-10-12Model interpretability in Azure ML Studio1:2794
2020-10-11How Do I Test a Python Click App?4:57104
2020-10-10Foundations of Distributed Machine Learning with Azure ML Studio and AWS Sagemaker1:21:18308
2020-10-10How to kick off an Azure AutoML model training run2:3539Guide
2020-10-09Using Azure AutoML SDK from a Jupyter Notebook4:34366
2020-10-08Python for DevOps Stories and Techniques3:27:411,225
2020-10-01Advanced Testing Techniques in Python1:39:00510
2020-09-24How to use Python Virtual Environments3:10131
2020-09-20Serverless Lambda Functions with Cloud939:011,189
2020-09-19Learn to perform multi-cloud onboarding in Python48:12173
2020-09-19Computer Vision with ONNX, Coral, and other edge devices1:16:27328
2020-09-13ML+AI Cooking with Cloud Services1:26:03108
2020-09-12No Code & Low Code Business Analytics1:18:12274
2020-09-12Hands on AutoML and Computer Vision in a Nutshell1:19:48165Preview
2020-09-06MLOPs topics in the cloud1:37:25188
2020-09-05Hello World Introduction to Colab Notebook2:07201
2020-09-05Welcome to the Pragmatic AI Labs Channel0:49719
2020-09-05Learn optimization with greedy algorithms1:22:12751
2020-09-05Learn to build AWS CLI tools around Computer Vision1:20:4370
2020-08-31Build out a Flask ML prediction on AWS Cloud96:52516
2020-08-28Professional @Work: Logging and Monitoring31:1573Vlog
2020-08-26The Power of Functions in Python1:33:14401
2020-08-23Data Science from Zero walkthrough for NBA Dataset1:26:551,151Walkthrough
2020-08-23Cloud Containers on AWS from Zero with Python1:34:05167
2020-08-21AWS Command Line Tool Development from Zero in Python with Click1:43:261,093
2020-08-17Python For DevOps3:27:3567,691
2020-08-16Creating a command-line tool with Click8:02145
2020-08-16Cloud Continuous Delivery with Hugo and Cloud91:44:27179
2020-08-15Learn about Computer Vision Edge including DeepLens and AWS Sagemaker1:22:18119
2020-08-15What is Business Analytics and Data Science58:12117
2020-08-13Professional @Work26:1169
2020-08-10How to use Trello for project management4:30121
2020-08-09Create a Makefile2:408,694
2020-08-09Multi-Cloud DevOps Onboard Lecture1:05:22390
2020-08-08Computer Vision API to AutoML to Edge1:20:55101
2020-08-07Professional @Work #345:1044
2020-08-06add-lint-azure-pipelines3:532,227
2020-08-06Continuous Delivery with Azure Pipelines in Python3:282,165
2020-08-02Setup Azure Cloud Shell with Github4:54370
2020-08-02Building Computer Vision APIs with AWS Lambda1:23:28515
2020-07-31Professional @Work #323:4353
2020-07-26Pragmatic AI6:22106
2020-07-25Emerging Topics in Computer Vision1:19:581,132
2020-07-25What is Cloud Computing1:14:5560
2020-07-24Professionals at Work: Episode #248:1778
2020-07-18computer-vision-lecture-intro1:04:44109
2020-07-18cloud-computing-serverless1:20:0335
2020-07-18computer-vision-automl1:27:0866
2020-07-18computer-vision-review1:19:25115Review
2020-07-17Pragmatic AI Labs Live Stream34:1860
2020-07-16Big Data Tools in the Cloud1:36:2850
2020-07-11Distributed Computing in the Cloud1:19:3971
2020-07-11Live Coding Computer Vision Demo with Lambda1:20:3982
2020-07-04Tools59:3361
2020-06-10setup-azure-cloud-shell-github-actions10:221,218
2020-05-19Education in the time of Covid54:5745
2020-05-08Yagni: Noah and Matt meet with Olympic athlete Alfredo Deza1:33:3088
2020-04-18continuous-deploy1:14:10114
2020-04-17Knowledge Investing27:1165
2020-04-11ml-platforms1:17:3385
2020-04-11Covid 19 Analysis58:4693
2020-04-05data-proc20:25692
2020-04-04emr32:14119
2020-03-28gcp-functions45:13270
2020-03-24Lightbulb Trigger vs AWS Lambda2:0581
2020-03-21Serverless Data Engineering49:051,437
2020-03-14cloud9-lambda12:36238
2020-03-14step-functions8:1255
2020-03-14aws-lambda-hello18:25109
2020-03-07redshift-demo30:222,844
2020-03-07GCP Big Query K-Means Walkthrough15:502,264Walkthrough
2020-02-29AWS Glue + Athena36:51559
2020-02-18Learn to use a CUDA GPU to dramatically speed up code in Python.9:0667,531