If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Machine Learning
How to pick a machine learning model 2: Separating signal from noise
Part of the End-to-End Machine Learning School course library at http://e2eml.school See these concepts used in an End to End Machine Learning project: https://end-to-end-machine-learning.teachable.com/p/polynomial-regression-optimization/ Watch the rest of the How to Choose a Model serie
From playlist E2EML 171. How to Choose Model
Intro to Sets | Examples, Notation & Properties
Learning Objectives: 1) Identify examples of sets 2) Write sets without regard to order or repetition 3) Determine whether one set is a subset of another **************************************************** YOUR TURN! Learning math requires more than just watching videos, so make sure you
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)
What is the complement of a set? Sets in mathematics are very cool, and one of my favorite thins in set theory is the complement and the universal set. In this video we will define complement in set theory, and in order to do so you will also need to know the meaning of universal set. I go
From playlist Set Theory
Set-Roster vs Set-Builder notation
Learning Objectives: 1) Write a set with infinitely many elements using Set-Roster notation 2) Write a set using Set-Builder notation 3) Convert between these two different notations for sets. **************************************************** YOUR TURN! Learning math requires more tha
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)
Relations between two sets | Definition + First Examples
Learning Objectives: 1) Recognize "less than" as an example of a relation 2) Draw a visual picture of a relation 3) State the formal definition of a relation **************************************************** YOUR TURN! Learning math requires more than just watching videos, so make sur
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)
Arrays can be used as sets, but Julia has a dedicated Set() function that eliminates any duplicate entries, proper for use in set theorey.
From playlist The Julia Computer Language
How to find the compliment of a set using a venn diagram
http://www.freemathvideos.com In this playlist I show you how to understand set theory. I introduce sets as venn diagrams, mapping and as sets of numbers. With sets we look at how to find the union, compliment, and intersection of given sets. We introduce sets with two and three diagrams
From playlist Sets - Venn Diagrams
Stanford CS330 I Unsupervised Pre-Training:Contrastive Learning l 2022 I Lecture 7
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai To follow along with the course, visit: https://cs330.stanford.edu/ To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Chelsea Finn Computer
From playlist Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022
Evaluating NLP Models via Contrast Sets
Current NLP models are often "cheating" on supervised learning tasks by exploiting correlations that arise from the particularities of the dataset. Therefore they often fail to learn the original intent of the dataset creators. This paper argues that NLP models should be evaluated on Contr
From playlist Adversarial Examples
Supervised Contrastive Learning
The cross-entropy loss has been the default in deep learning for the last few years for supervised learning. This paper proposes a new loss, the supervised contrastive loss, and uses it to pre-train the network in a supervised fashion. The resulting model, when fine-tuned to ImageNet, achi
From playlist General Machine Learning
AI Weekly Update - March 15th, 20201 (#28)!
Thank you for watching! Please Subscribe! Content Links: Behavior from the Void: https://arxiv.org/pdf/2103.04551.pdf Barlow Twins: https://arxiv.org/pdf/2103.03230.pdf Pretrained Transformers as Universal Compute Engines: https://arxiv.org/pdf/2103.05247.pdf A New Lens on Understanding G
From playlist AI Research Weekly Updates
Notion Link: https://ebony-scissor-725.notion.site/Henry-AI-Labs-Weekly-Update-July-15th-2021-a68f599395e3428c878dc74c5f0e1124 Chapters 0:00 Introduction 2:18 Improvements in Video Modeling 6:08 Vokenization 7:31 HowTo100M Data 9:07 Teacher Learning 13:06 Interesting Distillation Ideas 17
From playlist AI Weekly Update - July 15th, 2021!
CLIP: Connecting Text and Images
This video explains how CLIP from OpenAI transforms Image Classification into a Text-Image similarity matching task. This is done with Contrastive Training and Zero-Shot Pattern-Exploiting Training. Thanks for watching! Paper Links: Clip (Blog Post): https://openai.com/blog/clip/ VirTex:
From playlist AI Research Weekly Updates
AI Weekly Update - December 14th, 2020 (#24)!
Thank you for watching! Please Subscribe! Paper / Content Links: Abstraction & Reasoning in Modern AI Systems: https://slideslive.com/38935790/abstraction-reasoning-in-ai-systems-modern-perspectives Neurosymbolic AI: The 3rd Wave: https://arxiv.org/pdf/2012.05876.pdf On the Binding Proble
From playlist AI Research Weekly Updates
Transformer (Attention is all you need)
understanding Transformer with its key concepts (attention, multi head attention, positional encoding, residual connection label smoothing) with example. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6
From playlist Machine Learning
AI Weekly Update - May 20th, 2020 (#21)
Thank you for watching! Please Subscribe! I apologize about the Audio Quality, I had the mic too close to my mouth and didn't realize this until I finished editing the video. I didn't have the energy to re-record this episode, but will fix this in the future. Thanks for understanding, I ho
From playlist AI Research Weekly Updates
AI Weekly Update - February 17th, 2020 (#16)
ZeRO & DeepSpeed: https://www.microsoft.com/en-us/research/blog/zero-deepspeed-new-system-optimizations-enable-training-models-with-over-100-billion-parameters/ Turing-NLG: https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/?OCID=msr
From playlist AI Research Weekly Updates
AI Weekly Update - January 31st, 2022
Thank you so much for watching, please subscribe for more Deep Learning and Ai videos! Please check out SeMI Technologies on YouTube as well, where I am hosting a podcast on Deep Learning for Search! Paper Links: Text and Code Embeddings by Contrastive Pre-Training: https://cdn.openai.com
From playlist AI Research Weekly Updates
Formal Definition of a Function using the Cartesian Product
Learning Objectives: In this video we give a formal definition of a function, one of the most foundation concepts in mathematics. We build this definition out of set theory. **************************************************** YOUR TURN! Learning math requires more than just watching vid
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)