Trending repositories for topic kaggle
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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...
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tas...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
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...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tas...
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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...
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tas...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
goto_conversion - Used by 4+ Gold Medal Solutions on Kaggle
PyTorch extensions for fast R&D prototyping and Kaggle farming
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Fast and customizable framework for automatic ML model creation (AutoML)
Técnicas e recursos para estudar ciência de dados.
goto_conversion - Used by 4+ Gold Medal Solutions on Kaggle
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
A complete overview and insights into AI-Text detection :seedling: using the powerful BERT(Bi-directional encoder representation transformer) to predict if a text is AI-generated :sunflower: or Human-...
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
Papers and datasets for Vibration Analysis
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & comme...
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
PyTorch extensions for fast R&D prototyping and Kaggle farming
Một cuốn sách về Học Sâu đề cập đến nhiều framework phổ biến, được sử dụng trên 300 trường Đại học từ 55 đất nước bao gồm MIT, Stanford, Harvard, và Cambridge.
Fast and customizable framework for automatic ML model creation (AutoML)
A searchable compilation of Kaggle past solutions
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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...
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tas...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
Fast and customizable framework for automatic ML model creation (AutoML)
免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas suc...
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
Data Science projects on various problem statements and datasets using Data Analysis, Machine Learning Algorithms, Deep Learning Algorithms, Natural Language Processing, Business Intelligence concepts...
The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.
How to effectively finetune CV/LLM models (without local gpu)
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Técnicas e recursos para estudar ciência de dados.
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
Data Science projects on various problem statements and datasets using Data Analysis, Machine Learning Algorithms, Deep Learning Algorithms, Natural Language Processing, Business Intelligence concepts...
goto_conversion - Used by 4+ Gold Medal Solutions on Kaggle
An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.
Instructions for connecting SSH between Kaggle and Visual Studio Code
Papers and datasets for Vibration Analysis
Training RAVE, vschaos2, MSPrior and RAVE Latent Diffusion models on Kaggle or Colab
The pioneering neural network surpassing extremely-tuned XGboost and Catboost on varied tabular datasets.
The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.
Cassava leaf disease classification with CNNs and Transformers (top-1% Kaggle solution)
Data Extraction (from https://stats.nba.com) and Processing Scripts to Produce the NBA Database on Kaggle (https://kaggle.com/wyattowalsh/basketball)
A complete overview and insights into AI-Text detection :seedling: using the powerful BERT(Bi-directional encoder representation transformer) to predict if a text is AI-generated :sunflower: or Human-...
AI-Generated Text Detection: A BERT-powered solution for accurately identifying AI-generated text. Seamlessly integrated, highly accurate, and user-friendly.🚀
Fast and customizable framework for automatic ML model creation (AutoML)
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
a way to SSH into Kaggle. If you don't like ngrok because of CC, checkout zrok branch which dose not require CC
Developed a sophisticated machine learning model capable of generating diverse interview questions aligned with specific topics, ensuring depth of conversation. Integrated advanced Natural Language Pr...
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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...
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tas...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
Fast and customizable framework for automatic ML model creation (AutoML)
A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas suc...
免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
1st Place Solution for LLM - Detect AI Generated Text Kaggle Competition
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Fast and customizable framework for automatic and quick Causal Inference in Python
A complete overview and insights into AI-Text detection :seedling: using the powerful BERT(Bi-directional encoder representation transformer) to predict if a text is AI-generated :sunflower: or Human-...
Instructions for connecting SSH between Kaggle and Visual Studio Code
Fast and customizable framework for automatic and quick Causal Inference in Python
How to effectively finetune CV/LLM models (without local gpu)
AI-Generated Text Detection: A BERT-powered solution for accurately identifying AI-generated text. Seamlessly integrated, highly accurate, and user-friendly.🚀
Stable-Diffusion-WebUI - NoteBook | Colab (Pro/Free), Kaggle.
Detecting Fraudulent Blockchain Accounts on Ethereum with Supervised Machine Learning
1st Place Solution for LLM - Detect AI Generated Text Kaggle Competition
The Google Advanced Data Analytics Certificate contains information on how to use machine learning, predictive modeling, and experimental design to collect and analyze large amounts of data, and prepa...
goto_conversion - Used by 4+ Gold Medal Solutions on Kaggle
The pioneering neural network surpassing extremely-tuned XGboost and Catboost on varied tabular datasets.
Fast and customizable framework for automatic ML model creation (AutoML)
Training RAVE, vschaos2, MSPrior and RAVE Latent Diffusion models on Kaggle or Colab
Machine learning models to predict realtime financial market data provided by Jane Street
Data Science projects on various problem statements and datasets using Data Analysis, Machine Learning Algorithms, Deep Learning Algorithms, Natural Language Processing, Business Intelligence concepts...