Statistics for topic scipy
RepositoryStats tracks 518,989 Github repositories, of these 91 are tagged with the scipy topic. The most common primary language for repositories using this topic is Python (52). Other languages include: Jupyter Notebook (25)
Stargazers over time for topic scipy
Most starred repositories for topic scipy (view more)
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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...
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
🐳 Проектная деятельность. Здесь хранятся лекции, практические задания и проекты с karpov_courses. Ссылка: https://karpov.courses/
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and...
a numpy-like fast vector module for micropython, circuitpython, and their derivatives
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...
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and...
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and...
🐳 Проектная деятельность. Здесь хранятся лекции, практические задания и проекты с karpov_courses. Ссылка: https://karpov.courses/
Data Science + ML Cheat Sheet collection by me
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.
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...
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Formula Student Driverless Path Planning Algorithm. Colorblind centerline calculation algorithm developed by FaSTTUBe. It introduces a novel approach that uses neither Delaunay Triangulation nor RRT.
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.
Some python workbooks with various topics from Computational Physics
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and...
"Computational Methods for Economists using Python", by Richard W. Evans. Tutorials and executable code in Python for the most commonly used computational methods in economics.
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...
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and...
IBM Data Science Professional Certificate
Formula Student Driverless Path Planning Algorithm. Colorblind centerline calculation algorithm developed by FaSTTUBe. It introduces a novel approach that uses neither Delaunay Triangulation nor RRT.
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.
🐳 Проектная деятельность. Здесь хранятся лекции, практические задания и проекты с karpov_courses. Ссылка: https://karpov.courses/