Appreciate it Knut @JagersbergKnut Many thanks indeed, so important to break down barriers to access with learning and sharing resources such as this. Thanks for sharing, much appreciated, S #SDGs #education
INNOVATION
-
Accessible Educational Resources for Sustainable Development Goals
By
–
Absolute pleasure Kate, me too! Great accessible resources here for good! Many thanks Sally #SDGs #education
-
Build AI-Powered Search with Cohere AI Platform
By
–
What are you waiting for? Get started with building your AI-powered search using Cohere AI. https://
dashboard.cohere.ai/welcome/regist
er?utm_source=influencer&utm_medium=social&utm_campaign=shubham
… -

Building AI-Powered Search Frontend with Streamlit Components
By
–
Step-5: Add @streamlit components to build a frontend for the search. Let's break it down what all we would need: 1. We need users to be able to input their search query.
2. Cohere's model to convert text to embedding.
3. Finding similar sentences based on Cosine similarity. -

Export Python Code from Playground to IDE
By
–
Step-4: Export the Python code from the Playground and paste it into an IDE.
-

Visualizing Embeddings for Semantic Search Understanding
By
–
Step-3: Visualize the embeddings in the playground to understand how semantic search works. Semantically similar sentences would be dots closer to each other and vice-versa.
-
Building Twitter Thread Search with Cohere Embed
By
–
Let's build a simple search example for finding twitter thread topics related to Y-Combinator. Step-1: Go to the "Embed" Section in Cohere's Playground. Here is the link –
-

Semantic Search: Understanding Meaning Beyond Keywords
By
–
Semantic search is based on the idea of understanding the meaning and context of the words used in a query, rather than just matching the exact keywords to the documents. It focuses on finding relevant results that match the user's intention, rather than matching the keywords.
-

Cohere AI Embeddings: Convert Text to Numerical Representations
By
–
Interested in building AI-powered search but don't know where to start? Introducing Embeddings by Cohere AI Embeddings are a way to represent the meaning of text in a numerical form. Cohere's model can convert texts to embeddings out-of-the-box. https://
dashboard.cohere.ai/welcome/regist
er?utm_source=influencer&utm_medium=social&utm_campaign=shubham
… -
Building Google-like AI Search Engine with Python
By
–
How to build Google-like AI-powered search using Python in 15 minutes? (A thread)