Learn to Love Working with Vector Embeddings
Unlock the power of machine learning. Our guides will help you conquer vector embeddings and build better applications.
Our Series
Natural Language Processing for Semantic Search
Learn how to build semantic search systems. From machine translation to question-answering.
Faiss: The Missing Manual
Learn the essentials of vector search and how to apply them in Faiss.
Vector Search in the Wild
Take a look at the hidden world of vector search and its incredible potential.
Embedding Methods for Image Search
Learn about the past, present, and future of image search, text-to-image, and more.
Algorithms & Libraries
Batch and Layer Normalization
BERTopic: The Future of Topic Modeling
Cross-Entropy Loss
Filtering: The Missing WHERE Clause in Vector Search
How to Explain ConvNet Predictions Using Class Activation Maps
Introduction to Transfer Learning
Semantic Search: Measuring Meaning From Jaccard to Bert
Softmax Activation Function: Everything You Need to Know
Transformers Are All You Need
Ludicrous BERT Search Speeds
Introduction to K-Means Clustering
K-Nearest Neighbor (KNN) Explained
Evaluation Measures in Information Retrieval
Testing p2 Pods, Vertical Scaling, and Collections
Weight Initialization Techniques in Neural Networks
Applications of Vector Search
Optimize Classifier Training with Vector Search
Embeddings to Identify Fake News
Time Series Analysis Through Vectorization
Language Embedding Models in Financial Services
Plagiarism Detection Using Transformers
How Machine Learning is Accelerating Life Sciences
Projects
Question Answering
Question Answering
Long Form Question Answering in Haystack
Retrievers for Question-Answering
Readers for Question-Answering
Vector Search 101
What will you build?
Upgrade your search or recommendation systems with just a few lines of code, or contact us for help.