mix_merkletree VS bitcoin_price_prediction

Compare mix_merkletree vs bitcoin_price_prediction and see what are their differences.

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mix_merkletree bitcoin_price_prediction
1 1
5 10
- -
0.0 0.0
almost 2 years ago about 3 years ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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.

mix_merkletree

Posts with mentions or reviews of mix_merkletree. We have used some of these posts to build our list of alternatives and similar projects.

bitcoin_price_prediction

Posts with mentions or reviews of bitcoin_price_prediction. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing mix_merkletree and bitcoin_price_prediction you can also consider the following projects:

ta - Technical Analysis Library using Pandas and Numpy

mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.

carbon-simulator - This is an open-source python package developed by Bancor Research. It is meant to assist in the design, testing, and validating of the Carbon Protocol.

NYU-DLSP20 - NYU Deep Learning Spring 2020

TrainInvaders - 👾 Jupyter Notebook + Space Invaders!?

it-salary-analysis - 💰 Analysis of Salaries in IT Roles: DevOps, Cyber Security, and AI

Python-Bible - Resourceful Python Collection

Animender - An AI that recommends anime based on personal history.

biggestwar_ai

Anomaly_Detection_Tuto - Anomaly detection tutorial on univariate time series with an auto-encoder

peacasso - UI interface for experimenting with multimodal (text, image) models (stable diffusion).

diversity_measures - Code for the paper: Diversity Measures: Domain Independent Proxies for Failure in Language Model Queries