LLMs Explained - Aggregate Intellect - AI.SCIENCE

LLMs Explained - Aggregate Intellect - AI.SCIENCE

Views:
816,922
Subscribers:
20,400
Videos:
723
Duration:
20:17:30:40
Canada
Canada

LLMs Explained - Aggregate Intellect - AI.SCIENCE is a Canadian YouTube channel which has roughly 20.4 thousand subscribers, with his content totaling around 816.92 thousand views views across 723 videos.

Created on ● Channel Link: https://www.youtube.com/@ai-science



Top 100 Most Controversial Videos by LLMs Explained - Aggregate Intellect - AI.SCIENCE


Video TitleRatingCategoryGame
1.Modern Anomaly and Novelty Detection: Review - Session 210Review
2.Azure MLops- MLops Flow- Session II, part 10
3.Reinforcement Learning: Deep Q-Learning Q&A - Session 90
4.RPA for Enterprises0
5.Mathematics of Deep Learning: Convnets- Session 90
6.Azure MLops- ML Pipelines- Session III, part 10
7.Modern Anomaly and Novelty Detection: Deep Learning III - Session 200
8.Modern Anomaly and Novelty Detection: Classical ML Techniques I - Session 110
9.AI Product, Part 8: Short-term Validation0
10.Azure MLops- Experiment Reproducibility Hands-on III- Session II, part 40
11.Azure MLops- Experiment Reproducibility Hands-on I- Session II, part 20
12.Modern Anomaly and Novelty Detection: Exercise - Session 90
13.How do our community groups work?0
14.Private Investing in Deep Tech - DRT - S2 bonus ep - Ft. Moien Giashi, Darryl Kirsch, Hessie Jones0
15.Machine Learning for Cyber Security - Session 150
16.MLOps: Containerizing Flask and model, Session 3, part 10
17.Machine Learning for Cyber Security - Session 110
18.Modern Anomaly and Novelty Detection: Exercise - Session 130
19.MLOps: Serve a container on AWS ec2, Session 3, part 30
20.Modern Anomaly and Novelty Detection: Exercise - Session 240
21.Machine Learning for Cyber Security: Graphs in CS - Session 130
22.Modern Anomaly and Novelty Detection: Exercise - Session 250
23.Modern NLP: Low-level Text Processing- Session 1, part 20Let's Play
24.Azure MLops- Git Hands-on III- Session I, part 40
25.Modern Anomaly and Novelty Detection: Exercise - Session 170
26.Reinforcement Learning in the Real World (with Professor Matthew Taylor)0
27.Semi Supervised Learning - Session 50
28.Modern Anomaly and Novelty Detection: Exercise - Session 80
29.Machine Learning for Cyber Security - Session 170
30.Machine Learning for Cyber Security - Session 70
31.Modern Anomaly and Novelty Detection: Statistical Methods - Session 30
32.Modern Anomaly and Novelty Detection: Exercise - Session 140
33.Modern Anomaly and Novelty Detection: Exercise - Session 160
34.Reinforcement Learning: Q&A, Closing - Session 160
35.Semi Supervised Learning - Session 80
36.Azure MLops- Introduction- Session I, part I0
37.Machine Learning for Cyber Security - Session 100
38.Semi Supervised Learning - Session 90
39.Machine Learning for Cyber Security - Session 180
40.Modern Anomaly and Novelty Detection: Deep Learning II - Session 190
41.Learn about Foodshake and it’s vegan recipes!0
42.Azure MLops- Experiment Reproducibility Hands-on II- Session II, part 30
43.Machine Learning for Cyber Security - Session 80
44.Modern Anomaly and Novelty Detection: Classical ML Techniques II - Session 120
45.Semi Supervised Learning - Session 100
46.Modern Anomaly and Novelty Detection: Exercise - Session 230
47.Modern Anomaly and Novelty Detection: Exercise - Session 50
48.Modern NLP: Second Surge of NLP - Session 3, part 40
49.Machine Learning for Cyber Security - Session 160
50.Modern Anomaly and Novelty Detection: Exercise - Session 150
51.Azure MLops- MLPipeline_MNIST Hands-on- Session II, part 50
52.Semi Supervised Learning - Session 70
53.Azure MLops- Git Hands-on V, Experiments Intro- Session I, part 60
54.Azure MLops- Git Hands-on II- Session I, part 30
55.Modern Anomaly and Novelty Detection: Exercise - Session 220
56.Machine Learning for Cyber Security - Session 90
57.Machine Learning for Cyber Security - Session 40
58.Modern Anomaly and Novelty Detection: Exercise - Session 60
59.Azure MLops- Model Deployment- Session III, part 20
60.Role of Human Factors in Adoption of Generative AI in Life Sciences1
61.Reinforcement Learning: AI Gym Environment - Session 151
62.Why Collaborative Models are the Future of AI in Agriculture1
63.What is the relationship between language and intelligence?1
64.Reinforcement Learning: Policy Gradients - Session 121
65.Challenges and Solutions for LLMs in Production1
66.MLOps: Onnx Hands On, Session 2, part 51
67.Semi Supervised Learning - Session 111
68.Modern Anomaly and Novelty Detection: Exercise - Session 71
69.How Do You choose between training, fine-tuning, and using small models?1
70.Detecting and Correcting Unfairness in Machine Learning | AISC1
71.Machine Learning for Cyber Security - Session 31
72.Product Ideation: From a Hunch to a Concrete Idea1
73.Modern NLP: Second Surge of NLP - Session 3, part 31
74.Mathematics of Deep Learning: Gradient descent - Session 111
75.Council: A Framework for Developing Generative AI Applications2
76.Reinforcement Learning: Code Walkthrough - Session 31Walkthrough
77.An Overview: Sustainability Analysis Framework and Influences of AI on the Sustainability Dimensions1
78.Azure MLops- Git Hands-on IV- Session I, part 51
79.Azure MLops- MLops Flow- Session III, part 41
80.Reinforcement Learning: Fundamentals II - Session 41
81.Reinforcement Learning: Q-Learning - Session 71
82.Modern Anomaly and Novelty Detection: Exercise - Session 101
83.Streamflow Prediction in the Canadian Prairies1
84.Azure MLops- Git Hands-on I- Session I, part 21
85.Reinforcement Learning - Session 51
86.Generative AI: Ethics, Accessibility, Legal Risk Mitigation1
87.AI Product, Part 6: Product Team1
88.Azure MLops- Model Deployment II- Session III, part 31
89.Semi Supervised Learning - Session 41
90.Building ResearchLLM: automated statistical research and interpretation1
91.Modern Anomaly and Novelty Detection: Deep Learning I - Session 181
92.Machine Learning for Cyber Security- Introduction - Session 61
93.Building a chatbot infrastructure - MLOPs-fun1
94.Parallel Collaborative Filtering for the Netflix Prize (results & discussion) AISC Foundational1Discussion
95.SHERPA - Open Source Project Update, 2023-09-291Vlog
96.Forging the future of Geological Mapping with Machine Learning1Vlog
97.Environmental Data Science Workshops1
98.Eliciting Business Insights at Scale with Conversational AI5
99.Mathematics of Deep Learning: Linear Algebra III: non-linearities - Session 41
100.Reinforcement Learning: Applications Discussions - Session 141Discussion