Could a probiotic prevent autoimmune disease? The role of L. johnsonii in mitigating Type 1 Diabetes
Rachel Thomas
Could a probiotic prevent autoimmune disease? The role of L. johnsonii in mitigating Type 1 Diabetes
11:25
Deep Learning Applied to Immunology
Rachel Thomas
Deep Learning Applied to Immunology
33:27
How friendly gut bacteria could turn your immune system against you
Rachel Thomas
How friendly gut bacteria could turn your immune system against you
4:47
Machine Learning to Identify Lab-of-Origin for Genetic Sequences
Rachel Thomas
Machine Learning to Identify Lab-of-Origin for Genetic Sequences
14:45
Genetic risk, autoimmunity, and the gut microbiome
Rachel Thomas
Genetic risk, autoimmunity, and the gut microbiome
25:58
Journal Club: AlphaFold
Rachel Thomas
Journal Club: AlphaFold
15:22
You CAN and SHOULD get involved with AI
Rachel Thomas
You CAN and SHOULD get involved with AI
24:24
Tech Ethics Practices to Implement at your Workplace
Rachel Thomas
Tech Ethics Practices to Implement at your Workplace
6:20
Foundations of Ethics
Rachel Thomas
Foundations of Ethics
8:31
Advanced Technology is not a Substitute for Good Policy
Rachel Thomas
Advanced Technology is not a Substitute for Good Policy
13:36
What You Need to Know about Disinformation
Rachel Thomas
What You Need to Know about Disinformation
18:53
How to Address the Machine Learning Diversity Crisis
Rachel Thomas
How to Address the Machine Learning Diversity Crisis
9:06
7 Questions to Ask About Your Machine Learning Project
Rachel Thomas
7 Questions to Ask About Your Machine Learning Project
8:31
Humans are biased too, so why does machine learning bias matter?
Rachel Thomas
Humans are biased too, so why does machine learning bias matter?
8:09
Not all types of bias are fixed by diversifying your dataset
Rachel Thomas
Not all types of bias are fixed by diversifying your dataset
21:45
The Problem with Metrics, Feedback Loops, and Hypergrowth
Rachel Thomas
The Problem with Metrics, Feedback Loops, and Hypergrowth
12:54
All machine learning systems need ways to identify & address mistakes
Rachel Thomas
All machine learning systems need ways to identify & address mistakes
7:07
What are Ethics and Why do they Matter? Machine Learning Edition
Rachel Thomas
What are Ethics and Why do they Matter? Machine Learning Edition
13:00
AI, Medicine, and Bias: Diversifying Your Dataset is Not Enough
Rachel Thomas
AI, Medicine, and Bias: Diversifying Your Dataset is Not Enough
17:24
Disinformation & Coronavirus (Data Ethics Lesson 1.1)
Rachel Thomas
Disinformation & Coronavirus (Data Ethics Lesson 1.1)
1:38:25
Intro to Language Modeling (NLP video 8)
Rachel Thomas
Intro to Language Modeling (NLP video 8)
40:58
Text generation algorithms (NLP video 14)
Rachel Thomas
Text generation algorithms (NLP video 14)
25:40
Transfer learning (NLP video 9)
Rachel Thomas
Transfer learning (NLP video 9)
1:35:17
Introduction to the Transformer (NLP video 17)
Rachel Thomas
Introduction to the Transformer (NLP video 17)
22:54
Seq2Seq Translation (NLP video 12)
Rachel Thomas
Seq2Seq Translation (NLP video 12)
59:42
The Transformer for language translation (NLP video 18)
Rachel Thomas
The Transformer for language translation (NLP video 18)
55:17
ULMFit for non-English Languages (NLP Video 10)
Rachel Thomas
ULMFit for non-English Languages (NLP Video 10)
1:49:22
Revisiting Naive Bayes, and Regex (NLP video 7)
Rachel Thomas
Revisiting Naive Bayes, and Regex (NLP video 7)
37:34
Word embeddings quantify 100 years of gender & ethnic stereotypes-- Nikhil Garg (NLP video 13)
Rachel Thomas
Word embeddings quantify 100 years of gender & ethnic stereotypes-- Nikhil Garg (NLP video 13)
47:17
Sentiment Classification with Naive Bayes & Logistic Regression, contd. (NLP video 5)
Rachel Thomas
Sentiment Classification with Naive Bayes & Logistic Regression, contd. (NLP video 5)
51:29
Understanding RNNs (NLP video 11)
Rachel Thomas
Understanding RNNs (NLP video 11)
33:17
Algorithmic Bias (NLP video 16)
Rachel Thomas
Algorithmic Bias (NLP video 16)
1:26:17
Topic Modeling with SVD & NMF (NLP video 2)
Rachel Thomas
Topic Modeling with SVD & NMF (NLP video 2)
1:06:40
What you need to know about Disinformation (NLP video 19)
Rachel Thomas
What you need to know about Disinformation (NLP video 19)
51:22
Derivation of Naive Bayes & Numerical Stability (NLP video 6)
Rachel Thomas
Derivation of Naive Bayes & Numerical Stability (NLP video 6)
23:57
Implementing a GRU (NLP video 15)
Rachel Thomas
Implementing a GRU (NLP video 15)
23:14
What is NLP? (NLP video 1)
Rachel Thomas
What is NLP? (NLP video 1)
22:42
Sentiment Classification with Naive Bayes (NLP video 4)
Rachel Thomas
Sentiment Classification with Naive Bayes (NLP video 4)
58:20
Topic Modeling & SVD revisited (NLP video 3)
Rachel Thomas
Topic Modeling & SVD revisited (NLP video 3)
33:06
How to Learn Deep Learning (when you’re not a computer science PhD)
Rachel Thomas
How to Learn Deep Learning (when you’re not a computer science PhD)
20:10
There's no such thing as "not a math person"
Rachel Thomas
There's no such thing as "not a math person"
6:23
Computational Linear Algebra 10: QR Algorithm to find Eigenvalues, Implementing QR Decomposition
Rachel Thomas
Computational Linear Algebra 10: QR Algorithm to find Eigenvalues, Implementing QR Decomposition
1:36:31
Computational Linear Algebra 9: PageRank with Eigen Decompositions
Rachel Thomas
Computational Linear Algebra 9: PageRank with Eigen Decompositions
1:39:59
Word Embeddings, Bias in ML, Why You Don't Like Math, & Why AI Needs You
Rachel Thomas
Word Embeddings, Bias in ML, Why You Don't Like Math, & Why AI Needs You
2:08:37
Computational Linear Algebra 8: Numba, Polynomial Features, How to Implement Linear Regression
Rachel Thomas
Computational Linear Algebra 8: Numba, Polynomial Features, How to Implement Linear Regression
1:35:49
Computational Linear Algebra 7: Compressed Sensing for CT Scans
Rachel Thomas
Computational Linear Algebra 7: Compressed Sensing for CT Scans
1:37:03
Computational Linear Algebra 6: Block Matrix Mult, Broadcasting, & Sparse Storage
Rachel Thomas
Computational Linear Algebra 6: Block Matrix Mult, Broadcasting, & Sparse Storage
1:45:58
Computational Linear Algebra 5: Robust PCA & LU Factorization
Rachel Thomas
Computational Linear Algebra 5: Robust PCA & LU Factorization
1:40:59
Computational Linear Algebra 4: Randomized SVD & Robust PCA
Rachel Thomas
Computational Linear Algebra 4: Randomized SVD & Robust PCA
1:31:16
Computational Linear Algebra 3: Review, New Perspective on NMF, & Randomized SVD
Rachel Thomas
Computational Linear Algebra 3: Review, New Perspective on NMF, & Randomized SVD
1:41:14
Computational Linear Algebra 2: Topic Modelling with SVD & NMF
Rachel Thomas
Computational Linear Algebra 2: Topic Modelling with SVD & NMF
1:40:44
Computational Linear Algebra 1: Matrix Math, Accuracy, Memory, Speed, & Parallelization
Rachel Thomas
Computational Linear Algebra 1: Matrix Math, Accuracy, Memory, Speed, & Parallelization
1:42:57
Bias + Artificial Intelligence (in Medicine)
Rachel Thomas
Bias + Artificial Intelligence (in Medicine)
13:53
How to Learn Deep Learning when you are not a CS PhD
Rachel Thomas
How to Learn Deep Learning when you are not a CS PhD
20:06
AI + Impact: Rachel's story of co-founding fast.ai
Rachel Thomas
AI + Impact: Rachel's story of co-founding fast.ai
7:18
Deep Learning: More than a Fad
Rachel Thomas
Deep Learning: More than a Fad
5:48