introducing-python VS bootcamp

Compare introducing-python vs bootcamp and see what are their differences.

bootcamp

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc. (by milvus-io)
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introducing-python bootcamp
5 25
740 1,725
- 4.2%
0.0 9.4
almost 4 years ago 4 days ago
Python HTML
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

introducing-python

Posts with mentions or reviews of introducing-python. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-12.

bootcamp

Posts with mentions or reviews of bootcamp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-05-20.
  • FLaNK-AIM: 20 May 2024 Weekly
    28 projects | dev.to | 20 May 2024
  • FLaNK AI - 01 April 2024
    31 projects | dev.to | 1 Apr 2024
  • FLaNK Stack Weekly 22 January 2024
    37 projects | dev.to | 22 Jan 2024
  • Milvus Adventures Jan 5, 2023
    1 project | dev.to | 5 Jan 2024
    Metadata Filtering with Zilliz Cloud Pipelines This tutorial discuss scalar or metadata filtering and how you can perform metadata filtering in Zilliz Cloud. This blog continues on the previous blog on Getting started with RAG in just 5 minutes. You can find its code in this notebook and scroll down to Cell #27.
  • Build a search engine, not a vector DB
    3 projects | news.ycombinator.com | 20 Dec 2023
    Partially agree.

    Vector DBs are critical components in retrieval systems. What most applications need are retrieval systems, rather than building blocks of retrieval systems. That doesn't mean the building blocks are not important.

    As someone working on vector DB, I find many users struggling in building their own retrieval systems with building blocks such as embedding service (openai,cohere), logic orchestration framework (langchain/llamaindex) and vector databases, some even with reranker models. Putting them together is not as easy as it looks. A fairly changeling system work. Letting alone quality tuning and devops.

    The struggle is no surprise to me, as tech companies who are experts on this (google,meta) all have dedicated teams working on retrieval system alone, making tons of optimizations and develop a whole feedback loop of evaluating and improving the quality. Most developers don't get access to such resource.

    No one size fits all. I think there shall exist a service that democratize AI-powered retrieval, in simple words the know-how of using embedding+vectordb and a bunch of tricks to achieve SOTA retrieval quality.

    With this idea I built a Retrieval-as-a-service solution, and here is its demo:

    https://github.com/milvus-io/bootcamp/blob/master/bootcamp/R...

    Curious to learn your thoughts.

  • Vector Database in a Jupyter Notebook
    1 project | news.ycombinator.com | 6 Jun 2023
    Although it's common to use vector databases in conjunction with LLMs, I like to talk about vector databases in the context of unstructured data, i.e. any data that you can vectorize with (or without) an ML model. Yes, this includes text, but it also includes things like visual data, molecular structures, and geospatial data.

    For folks who want to learn a bit more, there are examples of vector database use cases beyond semantic text search in our bootcamp: https://github.com/milvus-io/bootcamp

  • Beginner-ish resources for choosing a vector database?
    1 project | /r/vectordatabase | 20 May 2023
    Easy to get started: Here are some tutorials for Milvus in a Jupyter Notebook that I wrote - reverse image search, semantic text search
  • Semantic Similarity Search
    1 project | /r/learnmachinelearning | 13 May 2023
    I think you can just store your vector embeddings in the vector store somewhere and then query with your second document. I created a short tutorial on this that shows how to get the top 2 vector embeddings from a text query
  • [D] Looking for open source projects to contribute
    15 projects | /r/MachineLearning | 9 Jan 2022
    For more beginner tasks associated with the Milvus vector database, you can contribute to the Bootcamp project( https://github.com/milvus-io/bootcamp), where we build a lot of data-driven solutions using ML and Milvus vector database, including reverse image search, recommender systems, etc.
  • I built an image similarity search system... Suggestions needed: what are some fun image datasets or scenarios I can use with this? :)
    3 projects | /r/datascience | 21 Dec 2021
    Source code here: https://github.com/milvus-io/bootcamp/tree/master/solutions/reverse_image_search

What are some alternatives?

When comparing introducing-python and bootcamp you can also consider the following projects:

Maze-PathFinder-Visualization-Python - 2D maze path solver visualizer implemented with python

Milvus - A cloud-native vector database, storage for next generation AI applications

google-research - Google Research

docarray - Represent, send, store and search multimodal data

es-clip-image-search - Sample implementation of natural language image search with OpenAI's CLIP and Elasticsearch or Opensearch.

habitat-sim - A flexible, high-performance 3D simulator for Embodied AI research.

annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

nn - 🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.

html_tag_annotator - A Machine Learning tool to create the training dataset very quickly & easily by using a smart chrome extension

vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

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Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.
www.scoutapm.com
featured
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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