A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)
Inspired by CS50's Introduction to Artificial Intelligence
pip install - r requirements.txtNaive-Bayes Spam Classificator Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
torque_model The torque model is a spiritual successor to op-smart-torque, which was a project to train a neural network to control a car's steering f
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
About Solve CTF offline disconnection problem - based on python3's small crawler, support keyword search and local map bed establishment, currently support Jianshu, xianzhi,anquanke,freebuf,seebug
PyHarmonize: Adding harmony lines to recorded melodies in Python About To use this module, the user provides a wav file containing a melody, the key i
Cryptocurrency price prediction and exceptions in python This is a coursework on foundations of computing module Through this coursework i worked on m
CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c
KU AIRS: SPARK Autonomous Vehicle Project Check this link for the blog post describing this project and the video of SPARK in simulation and on parkou
基于马尔可夫链的写作机器人 前端 用html/css完成 Demo展示（已给出文本的相应展示） 用户提供相关的语料库后训练的成果 后端 要完成的几个接口 解析文
sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model
Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version
fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art
ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from
AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast
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