AI-Expert-Roadmap
spaCy
| AI-Expert-Roadmap | spaCy | |
|---|---|---|
| 30 | 107 | |
| 28,597 | 28,978 | |
| 0.6% | 0.6% | |
| 0.0 | 9.1 | |
| 5 months ago | 3 days ago | |
| JavaScript | Python | |
| MIT License | MIT License |
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.
AI-Expert-Roadmap
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Best AI ML DL DS Roadmap
**[I.am.ai AI Expert Roadmap](https://i.am.ai/roadmap)**: This roadmap focuses more on AI and includes various aspects of machine learning and deep learning. It's suitable for those who want to delve deeper into AI, particularly in cutting-edge research and applications.
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[D] Best AI ML DL DS Roadmap
Some roadmaps I have found: - [roadmap.sh] AI and Data Scientist Roadmap ← Best? - [i.am.ai] AI Expert Roadmap - [github.com] mrdbourke/machine-learning-roadmap - [github.com] luspr/awesome-ml-courses - [rentry.org] Machine Learning Roadmap
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[D] Roadmap.sh vs Al Expert Roadmap
[i.am.ai] AI Expert Roadmap
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Suggest which roadmap should I follow for ML?
1.https://i.am.ai/roadmap
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Where can I start?
I recommend this site where there's a roadmap for becoming an AI expert: https://i.am.ai/roadmap
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Can some one suggest Top certification courses for AI ?
Currently, I'm also learning about AI from this source https://github.com/AMAI-GmbH/AI-Expert-Roadmap
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How to study Machine Learning effectively?
I suggest following this roadmap. You might be put off by the amount of statistics topics, but it truly underpins almost all of machine learning so it's definitely useful to know.
- Como meterme al mundo AI
- Aprender IA siendo Programador?
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Mlops roadmap
Also: https://i.am.ai/roadmap/
spaCy
- How I discovered Named Entity Recognition while trying to remove gibberish from a string.
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Step by step guide to create customized chatbot by using spaCy (Python NLP library)
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):
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Best AI SEO Tools for NLP Content Optimization
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging.
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Who has the best documentation you’ve seen or like in 2023
spaCy https://spacy.io/
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A beginner’s guide to sentiment analysis using OceanBase and spaCy
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy.
- Retrieval Augmented Generation (RAG): How To Get AI Models Learn Your Data & Give You Answers
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Against LLM Maximalism
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post.
The steps described in "LLM pragmatism" are basically what I see my data science friends doing — it's hard to justify the cost (money and latency) in using LLMs directly for all tasks, and even if you want to you'll need a baseline model to compare against, so why not use LLMs for dataset creation or augmentation in order to train a classic supervised model?
[0] https://spacy.io/
[1] https://prodi.gy/
- Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
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How to predict this sequence?
spaCy
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What do you all think about (setq sentence-end-double-space nil)?
I chose spacy. Although it's not state of the art, it's very well established and stable.
What are some alternatives?
developer-roadmap - Interactive roadmaps, guides and other educational content to help developers grow in their careers.
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
dalle-playground - A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
NLTK - NLTK Source
igel - a delightful machine learning tool that allows you to train, test, and use models without writing code
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
arbitrary-image-stylization-tfjs - Arbitrary style transfer using TensorFlow.js
polyglot - Multilingual text (NLP) processing toolkit
LeetCode - This is my LeetCode solutions for all 2000+ problems, mainly written in C++ or Python.
textacy - NLP, before and after spaCy