Trending repositories for topic pandas
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
Python Data Science Handbook: full text in Jupyter Notebooks
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Lightweight and extensible compatibility layer between dataframe libraries!
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Modin: Scale your Pandas workflows by changing a single line of code
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Lightweight and extensible compatibility layer between dataframe libraries!
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
动手实战人工智能系列教程，希望从监督学习开始，带你入门机器学习和深度学习。我尝试剖析和推导每一个基础算法的原理，将数学过程写出来，同时基于 Python 代码对公式进行实现，做到公式和代码的一一对应。与此同时，我也会利用主流的开源框架重复同样的过程，帮助读者看出手动实现和主流框架实现之间的区别。
📈 PatternPy: A Python package revolutionizing trading analysis with high-speed pattern recognition, leveraging Pandas & Numpy. Effortlessly spot Head & Shoulders, Tops & Bottoms, Supports & Resistanc...
Speech Emotion Recognition (SER) in real-time, using Deep Neural Networks (DNN) of Long Short Memory Term (LSTM).
Extract and visualize information from Gurobi log files
A lightweight library that leverages Language Models (LLMs) to enable natural language interactions, allowing you to source and converse with data.
A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing,...
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news article sentiment collected using APIs and web scraping.
简单易用的量化金融数据包(easy utility for getting financial market data of China)
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
Lightweight and extensible compatibility layer between dataframe libraries!
Modin: Scale your Pandas workflows by changing a single line of code
A simple package to abstract away the process of creating usable DataFrames for data analytics. This package is heavily inspired by the amazing Python library, Pandas.
Compare DuckDB, Polars and Pandas for generating an artificial dataset of persons and companies
Start developing and backtesting your own automated trading strategies
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
🟣 Pandas interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
Lightweight and extensible compatibility layer between dataframe libraries!
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare ...
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Speech Emotion Recognition (SER) in real-time, using Deep Neural Networks (DNN) of Long Short Memory Term (LSTM).
A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing,...
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
A lightweight library that leverages Language Models (LLMs) to enable natural language interactions, allowing you to source and converse with data.
Python package to scrape flight data from Google Flights and analyzes prices. Can determine optimal flight from date, place, and price
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Lightweight and extensible compatibility layer between dataframe libraries!
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
🦖 A SQL-on-everything Query Engine you can execute over multiple databases and file formats. Query your data, where it lives.
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare ...
Start developing and backtesting your own automated trading strategies
🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning t...
动手实战人工智能系列教程，希望从监督学习开始，带你入门机器学习和深度学习。我尝试剖析和推导每一个基础算法的原理，将数学过程写出来，同时基于 Python 代码对公式进行实现，做到公式和代码的一一对应。与此同时，我也会利用主流的开源框架重复同样的过程，帮助读者看出手动实现和主流框架实现之间的区别。
scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
A simple package to abstract away the process of creating usable DataFrames for data analytics. This package is heavily inspired by the amazing Python library, Pandas.
Lightweight and extensible compatibility layer between dataframe libraries!
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
📈 PatternPy: A Python package revolutionizing trading analysis with high-speed pattern recognition, leveraging Pandas & Numpy. Effortlessly spot Head & Shoulders, Tops & Bottoms, Supports & Resistanc...
A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing,...
Lightweight and extensible compatibility layer between dataframe libraries!
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
Start developing and backtesting your own automated trading strategies
Template to quickstart streaming analytics using Apache Kafka for ingestion, QuestDB for time-series storage and analytics, Grafana for near real-time dashboards, and Jupyter Notebook for data science
ML-algorithms from scratch using Python. Classic Machine Learning course.
A Python script that anonymizes an Excel file and synthesizes new data in its place.
7 Day AI ML Fundamentals Workshop The purpose of this FREE workshop is 1. To give you a boost of getting started with AI. 2. A life-long community with a similar mindset. 3. strong grip on fundamental...
This repository contains Python code for visualizing the Bank Marketing dataset using various data visualization techniques. The dataset is loaded from a CSV file, and both numerical and categorical f...
A YouTube analytics tool for trend, sentiment, and suitability insights.
🟣 Pandas interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning t...
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
10 Weeks, 20 Lessons, Data Science for All!
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing,...
动手实战人工智能系列教程，希望从监督学习开始，带你入门机器学习和深度学习。我尝试剖析和推导每一个基础算法的原理，将数学过程写出来，同时基于 Python 代码对公式进行实现，做到公式和代码的一一对应。与此同时，我也会利用主流的开源框架重复同样的过程，帮助读者看出手动实现和主流框架实现之间的区别。
A Python script that anonymizes an Excel file and synthesizes new data in its place.
A beginner's roadmap to self studying Machine Learning and Artificial Intelligence
scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.
This repository was created to showcase my analytical and technical skills (Excel, Python, SQL, Power BI, PowerPoint, and others).
This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.
This repository is to show my Data Analytics & Engineering skills, share projects, and track my progress.
Compare DuckDB, Polars and Pandas for generating an artificial dataset of persons and companies
7 Day AI ML Fundamentals Workshop The purpose of this FREE workshop is 1. To give you a boost of getting started with AI. 2. A life-long community with a similar mindset. 3. strong grip on fundamental...
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare ...
📈 PatternPy: A Python package revolutionizing trading analysis with high-speed pattern recognition, leveraging Pandas & Numpy. Effortlessly spot Head & Shoulders, Tops & Bottoms, Supports & Resistanc...
Entity Matching Model solves the problem of matching company names between two possibly very large datasets.
Python binding for Rust's library for reading excel and odf file - calamine.
