Tanmay Bakshi
Ranking Amazon Reviews by Quality with Pointwise Ratings learned from Pairwise Data
#1about 7 minutes
Ranking Amazon reviews by learning a quality score
The model learns to assign a continuous quality score to reviews by training on a classification task rather than a direct regression problem.
#2about 7 minutes
How neural networks learn through feature embeddings
Neural networks transform complex input data into a high-dimensional embedding space where it becomes linearly separable for classification.
#3about 6 minutes
Processing sequential text data with Word2Vec and RNNs
Word2Vec creates semantic vector representations of words, which are then processed sequentially by Recurrent Neural Networks (RNNs) to understand context.
#4about 5 minutes
Identifying the limitations of recurrent neural networks
Recurrent neural networks are slow due to their sequential nature, lack general-purpose understanding, and struggle to process bidirectional context simultaneously.
#5about 8 minutes
Introducing the BERT and transformer architecture
The Transformer architecture uses self-attention to process text in parallel, enabling BERT to learn general, contextual word representations through masked language modeling.
#6about 6 minutes
Demonstrating self-attention with a character-level model
A simplified character-level model called 'Artist BERT' demonstrates how self-attention works by predicting masked characters in artist names.
#7about 8 minutes
Training a pointwise ranker from pairwise review data
A Siamese network architecture processes pairs of reviews to determine which is better, implicitly learning a pointwise quality score for each individual review.
Related jobs
Jobs that call for the skills explored in this talk.
Wilken GmbH
Ulm, Germany
Senior
Kubernetes
AI Frameworks
+3
Picnic Technologies B.V.
Amsterdam, Netherlands
Intermediate
Senior
Python
Structured Query Language (SQL)
+1
Matching moments
04:57 MIN
Increasing the value of talk recordings post-event
Cat Herding with Lions and Tigers - Christian Heilmann
02:20 MIN
The evolving role of the machine learning engineer
AI in the Open and in Browsers - Tarek Ziadé
04:09 MIN
How Python became the dominant language for AI
AI in the Open and in Browsers - Tarek Ziadé
04:05 MIN
How AI code generators have become more reliable
AI in the Open and in Browsers - Tarek Ziadé
01:02 MIN
AI lawsuits, code flagging, and self-driving subscriptions
Fake or News: Self-Driving Cars on Subscription, Crypto Attacks Rising and Working While You Sleep - Théodore Lefèvre
02:49 MIN
Using AI to overcome challenges in systems programming
AI in the Open and in Browsers - Tarek Ziadé
00:59 MIN
Distinguishing real from fake tech headlines
Fake or News: Coding on a Phone, Emotional Support Toasters, ChatGPT Weddings and more - Anselm Hannemann
04:28 MIN
Building an open source community around AI models
AI in the Open and in Browsers - Tarek Ziadé
Featured Partners
Related Videos
How AI Models Get Smarter
Ankit Patel
What do language models really learn
Tanmay Bakshi
WeAreDevelopers LIVE - Vector Similarity Search Patterns for Efficiency and more
Chris Heilmann, Daniel Cranney, Raphael De Lio & Developer Advocate at Redis
Develop AI-powered Applications with OpenAI Embeddings and Azure Search
Rainer Stropek
A beginner’s guide to modern natural language processing
Jodie Burchell
How we built an AI-powered code reviewer in 80 hours
Yan Cui
Mastering Image Classification: A Journey with Cakes
Carly Richmonds
Overview of Machine Learning in Python
Adrian Schmitt
Related Articles
View all articles



From learning to earning
Jobs that call for the skills explored in this talk.

Imec
Azure
Python
PyTorch
TensorFlow
Computer Vision
+1

Amazon.com Inc.
XML
HTML
JSON
Python
Data analysis
+1

Amazon.com Inc.
XML
HTML
JSON
Python
Data analysis
+1

score4more GmbH
Berlin, Germany
Remote
Intermediate
API
Scrum
React
DevOps
+8


Amazon.com Inc.
Senior
R
API
Unix
Perl
Ruby
+7

Amazon.com, Inc
Shoreham-by-Sea, United Kingdom
XML
HTML
JSON
Python
Data analysis
+1


AppIQ Tech
Remote
Senior
NoSQL
React
Python
Appium
+10