Life & fun · alternatives · 2026

24 alternatives to Mixed Naive Bayes for categorical and continuous data, written in NumPy

Naive Bayes with support for categorical and continuous data - remykarem/mixed-naive-bayes

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Mixed Naive Bayes for categorical and continuous data, written in NumPy launched in 2019; newer entries below may have overtaken it.

1
Automated smooth Nth order derivatives of noisy data▲146
This little project came about because I kept running into the same problem: cleanly differentiating sensor data before doing analysis. There are a ton of ways to solve this problem, I've always personally been a fan of using kalman filters for the job as its easy to get the double whammy of resampling/upsampling to a fixed consistent rate and also smoothing/outlier rejection. I wrote a little numpy only bayesian filtering/smoothing library recently (https://github.com/hugohadfield/bayesfilter/) so this felt like a fun and very useful first thing to…
2024 · github.com · its alternatives →
2NL
Natural Language Processing Demystified▲286
Link: https://www.nlpdemystified.org/ Hi HN: After a year of work, I've published my free NLP course. The course helps anyone who knows Python and a bit of math go from the basics to today's mainstream models and frameworks. I strive to balance theory and practice, so every module consists of detailed explanations and slides along with a Colab notebook putting the ideas into practice (in most modules). The notebooks cover how to accomplish everyday NLP tasks including extracting key information, document search, text similarity, text classification, finding topics in…
2022 · its alternatives →
3
Natural Language Processing Demystified (Part One)▲166
Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…
2022 · nlpdemystified.org · its alternatives →
4AI
An Interactive Guide to Teach Derivatives and Backpropagation▲119
2023 · x0axz.com · its alternatives →
5
I implemented a neural network in SQL▲121
Two weeks ago I was on my babymoon in Corfu, Greece. While in transit, I was overseeing a GSoC intern submit an important feature to my array database library, Xarray-SQL. He added `to_dataset()`, which completed the roundtrip between thinking of array data in a tabular model simultaneously as gridded rasters (the premise of the project is that every Nd array can be mapped to 2d, where orthogonal dims of the Nd array are just primary keys of a tabular representation). We discussed in chat, now that this feature existed, what demos could we make that would prove this data model works? With…
Jul 2026 · github.com · its alternatives →
6
Naive Bayes classifier for text categorization in five steps▲7
Your home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.
2019 · towardsdatascience.com · its alternatives →
7
PyPOTS▲67
a Python lib for data mining on PartiallyObserved TimeSeries
2023 · pypots.com · its alternatives →
8
Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends▲57
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for…
2024 · github.com · its alternatives →
9
Python Machine Learning▲80
Learning machine learning has never been easier
2017 · amazon.com · its alternatives →
10
Word2vec Algorithm in ~100sloc with NumPy▲72
Here's a small demonstration of the fundamental aspects of the word-to-vec algorithm. It's implemented in a single python script and depends only on a single text file for training. It's not meant to be blazingly fast or anything, just a toy example to aid my understanding of how word vectors might be learnt from a corpus.
2023 · github.com · its alternatives →
11
Chat With Traders x Quantopian: Machine learning in finance▲60
5/6 · The workflow of a professional quant trading firm.
2016 · soundcloud.com · its alternatives →
12
Python SDK – forecasting with foundation time-series and tabular models▲43
We’ve built a Python SDK for running inference on foundation models designed for time-series and tabular data. They are new SOTA models for time-series and tabular tasks and work out of the box. They do not require model training or feature engineering. The link to the GitHub repository is: https://github.com/S-FM/faim-python-client
Dec 2025 · github.com · its alternatives →
13SF
Smart Fruit – A Python schema-based machine learning library▲44
I've made a small Python library, designed for quick-and-easy prototyping of machine learning models. It's built on top of scikit-learn, to serialize and deserialize data from the forms you're likely to have, to the format used in scikit-learn. https://github.com/madman-bob/Smart-Fruit It's pretty bare-bones at the moment, but I thought I'd see if there was any interest before spending too much time on it. Let me know what you think.
2018 · its alternatives →
14
Modular Diffusion – A modular Python library for diffusion models▲40
Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process…
2023 · github.com · its alternatives →
15NH
Nuanced – Help AI understand code structure, not just text▲34
Hi HN! We built Nuanced (https://github.com/nuanced-dev/nuanced), an open-source Python library that makes AI coding tools smarter about code structure. The problem: current AI coding assistants see code as just text. They don't understand which functions call which, or how code components depend on each other. This is why they often suggest changes that break dependencies they should have known about. Nuanced solves this by generating call graphs that map these relationships. When you ask "What would break if I change this function?", instead of guessing, the AI can see…
2025 · nuanced.dev · its alternatives →
16
A completely handwritten deep neural network in python▲13
A handwritten multilayer perceptron classifer using numpy. - meetvora/mlp-classifier
2016 · github.com · its alternatives →
17
How to Convert Numerical to Categorical Variables with Decision Trees▲5
How decision trees can be used to convert numerical variables into categorical variables and use R to bin data. Example data set with source code included.
2016 · blog.clevertap.com · its alternatives →
18
Spam classifier in Go using Naive Bayes▲29
Spam classifier in pure Go using Naive Bayes. Contribute to igomez10/nspammer development by creating an account on GitHub.
Nov 2025 · github.com · its alternatives →
19
MLonFHIR: Fusing Sklearn with the HL7 FHIR Standard▲13
A work in progress library that fuses the HL7 FHIR standard with scikit-learn - chrisby/ml-on-fhir
2020 · github.com · its alternatives →
20
lineflow – Simple NLP Data Loader for PyTorch, etc.▲5
:zap:A Lightweight NLP Data Loader for All Deep Learning Frameworks in Python - tofunlp/lineflow
2019 · github.com · its alternatives →
21
Lightly – A Python library for self-supervised learning on images▲5
A python library for self-supervised learning on images. - lightly-ai/lightly
2023 · github.com · its alternatives →
22
New Causal Impact Library▲9
Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow - YuminosukeSato/bsts-causalimpact
Mar 2026 · github.com · its alternatives →
23
CueObserve – Open-source Anomaly detection on SQL data▲9
Timeseries Anomaly detection and Root Cause Analysis on data in SQL data warehouses and databases - cuebook/CueObserve
2021 · github.com · its alternatives →
24IO
Implementation of Poincaré Embeddings(Facebook Research) in Numpy▲6
The implementation is at: https://github.com/nishnik/poincare_embeddings Corresponding blog post: https://medium.com/towards-data-science/facebook-research-ju... Corresponding paper: https://arxiv.org/abs/1705.08039 This paper explores Poincare disk model instead of Euclidean space for embedding hierarchical data
2017 · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →