Pragmatic AI Labs

Pragmatic AI Labs

Views:
591,448
Subscribers:
18,100
Videos:
1,163
Duration:
19:22:43:52
United States
United States

Pragmatic AI Labs is an American YouTube channel which has at least 18.1 thousand subscribers, publishing roughly 1.16 thousand videos which altogether total approximately 591.45 thousand views.

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



Top 100 Videos With The Longest Duration by Pragmatic AI Labs


Video TitleDurationCategoryGame
1.Free 4 Hour Live Bootcamp: Rust for Pythonistas3:36:24Rust
2.Python for DevOps Stories and Techniques3:27:41
3.Python For DevOps3:27:35
4.Python Functions Master Class 20233:12:07
5.Python Functions Master Class 20233:12:03
6.Key Skills Python DevOps Projects with Copilot3:00:12
7.Cutting Edge MLOps using Github Codespaces Hugging Face OpenAI and Copilot AI to Write AI2:52:58
8.Building logistics projects with GitHub ecosystem and Github Copilot2:51:42Vlog
9.Pytest Master Class Full Course2:46:31
10.Cloud-Native Pytest Tips and Tricks from Ground Zero2:39:17
11.Rust for Pythonista: Multi-hour Jam Session2:38:20
12.Rust for Pythonista-3hr-Jam-Session2:38:20
13.Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers and Microservices2:37:08
14.MLOps Masterclass: Theory to DevOps to Cloud-native to AutoML2:36:04
15.Six Key elements MLOps2:30:17
16.Python Functions2:30:07
17.MLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn2:26:24
18.Python for DevOps 2023: 3H Zero/Hero2:19:59
19.From Python to Rust(3HR-LiveCoding-Nov/2023)2:19:49
20.Functions from zero2:18:34
21.Build Real-World Python Microservices with Continuous Delivery From Zero2:10:42
22.MLOPs chronicles 11 20212:04:30
23.Logic to live2:01:58
24.Build Real-World AWS Microservices with Python and FastAPI From Zero1:59:51
25.Build Real-World Python Microservices with Continuous Delivery From Zero1:59:49
26.Key Skills Software Craftsmanship-10 Lessons1:44:35
27.Key Skills Software Craftsmanship-10 Lessons1:44:34
28.Key Skills Software Craftsmanship-10 Lessons1:44:33
29.Key Skills Software Craftsmanship-10 Lessons1:44:32
30.1 2 cloud computing service models1:44:27
31.Cloud Continuous Delivery with Hugo and Cloud91:44:27
32.python devops two hours1:44:09
33.Learn Python for DevOps in Two Hours1:44:07
34.AWS Command Line Tool Development from Zero in Python with Click1:43:26
35.Advanced Testing Techniques in Python1:39:00
36.1 7 continuous delivery for ml engineering1:37:25
37.Introduction to MLOps1:37:25
38.MLOPs topics in the cloud1:37:25
39.Big Data Tools in the Cloud1:36:28
40.Cloud Containers on AWS from Zero with Python1:34:05
41.1 6 containers in the cloud1:34:05
42.Python Functions: Inputs, Unit of Work, Return1:33:35
43.Yagni: Noah and Matt meet with Olympic athlete Alfredo Deza1:33:30
44.The Power of Functions in Python1:33:14
45.Chap7 walkthrough MLOps cookbook O'Reilly book Practical MLOps1:31:37Walkthrough
46.MLOps containers with AWS and GCP1:29:17
47.Github Action Tricks and Tips for Many Clouds1:28:05
48.The Rise of Linux Desktop for Professionals1:27:28
49.Live Stream: The Rise of Linux Desktop for Professionals1:27:27
50.computer-vision-automl1:27:08
51.Practical MLOPS Chap2 MLOps Foundations1:27:05
52.Practical MLOPS Chap2 MLOps Foundations1:27:03
53.Data Science from Zero walkthrough for NBA Dataset1:26:55Walkthrough
54.1 2 data visualization1:26:55
55.1 3 using ai apis in applied computer vision1:26:03
56.ML+AI Cooking with Cloud Services1:26:03
57.Optimization With AWS Step Functions1:25:52
58.Live coding Hugging Face with GitHub GPU Codespaces1:25:34
59.Building Computer Vision APIs with AWS Lambda1:23:28
60.1 5 build serverless solutions with cloud computing1:23:00
61.Learning Serverless1:23:00
62.AutoML KaizenML1:22:45
63.1 6 Using AWS for Computer Vision with AWS DeepLens and AWS Lambda1:22:18
64.Learn about Computer Vision Edge including DeepLens and AWS Sagemaker1:22:18
65.1 4 optimization greedy algorithms1:22:12
66.Learn optimization with greedy algorithms1:22:12
67.Foundations of Distributed Machine Learning with Azure ML Studio and AWS Sagemaker1:21:18
68.1 3 distributed computing in the cloud1:21:18
69.Ethical AI Conversation with Johan Cedmar-Brandstedt1:21:01
70.Computer Vision API to AutoML to Edge1:20:55
71.Learn to build AWS CLI tools around Computer Vision1:20:43
72.Live Coding Computer Vision Demo with Lambda1:20:39
73.cloud-computing-serverless1:20:03
74.Emerging Topics in Computer Vision1:19:58
75.Hands on AutoML and Computer Vision in a Nutshell1:19:48Preview
76.1 4 using AutoML in applied computer vision1:19:48
77.Distributed Computing in the Cloud1:19:39
78.computer-vision-review1:19:25Review
79.No Code & Low Code Business Analytics1:18:12
80.1 5 building data science solutions1:18:12
81.ml-platforms1:17:33
82.LiveStream MLOps Talk1:17:28
83.MLOps with Head of Duke Artificial Intelligence PI MS Program1:17:25
84.1 2 emerging topics in applied computer vision1:17:20
85.Enterprise MLOps Interview Brian Ray1:17:12
86.Enterprise MLOps Interview Brian Ray-10 Steps to MLOps1:17:11
87.1 5 using edge computer vision hardware1:16:27
88.Computer Vision with ONNX, Coral, and other edge devices1:16:27
89.Story Telling with Data1:15:45
90.What is Cloud Computing1:14:55
91.Learn to Containerize Algorithms Deploy to AWS with App Runner1:14:41
92.Machine learning concepts1:14:12
93.continuous-deploy1:14:10
94.Optimization and Greedy Algorithms in One Hour1:13:46
95.Sagemaker from Zero County Cluster Demo1:13:36
96.1 0 from zero to one datascience to mlops1:12:41
97.Building Cloud ETL Pipelines1:12:01
98.1 4 cloud computing build etl pipelines1:12:01
99.Ville Tuulos-Metaflow-MLOps-Conversation1:11:49
100.Business Analytics and Data Science on Day 11:10:34