Trending repositories for topic scipy
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...
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Geostatistical variogram estimation expansion in the scipy style
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Geostatistical variogram estimation expansion in the scipy style
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
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...
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...
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
Forward modeling, inversion, and processing gravity and magnetic data
Geostatistical variogram estimation expansion in the scipy style
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
Forward modeling, inversion, and processing gravity and magnetic data
Geostatistical variogram estimation expansion in the scipy style
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
fit piecewise linear data for a specified number of line segments
Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
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 Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.
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 series of Jupyter notebooks and python files which stream audio from a microphone using pyaudio, then processes it.
Gcc for termux with fortran scipy etc... Use apt for newest updates instructions in README.txt
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
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.
Scientific Computing for Chemists is a free text for teaching basic computing skills to chemists using Python, Jupyter notebooks, and the other Python packages. This text makes use of a variety of pac...
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 Platform for Scientific and Technical Data Processing and Visualization
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
Data Science + ML Cheat Sheet collection by me
Sharing the solved Exercises & Project of Statistics for Data Science using Python course on Coursera by Ankit Gupta
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.
Hydrogen wavefunction modeling and electron probability density plots
A series of Jupyter notebooks and python files which stream audio from a microphone using pyaudio, then processes it.
Gcc for termux with fortran scipy etc... Use apt for newest updates instructions in README.txt
Scientific Computing for Chemists is a free text for teaching basic computing skills to chemists using Python, Jupyter notebooks, and the other Python packages. This text makes use of a variety of pac...
IBM Data Science Professional Certificate
Geostatistical variogram estimation expansion in the scipy style
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
Scikit-Criteria is a collection of Multiple-criteria decision analysis (MCDA) methods integrated into scientific python stack. Is Open source and commercially usable.
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 Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
A series of Jupyter notebooks and python files which stream audio from a microphone using pyaudio, then processes it.
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.
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 Platform for Scientific and Technical Data Processing and Visualization
Hydrogen wavefunction modeling and electron probability density plots
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.
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & S...
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.
Sharing the solved Exercises & Project of Statistics for Data Science using Python course on Coursera by Ankit Gupta
"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.
Scientific Computing for Chemists is a free text for teaching basic computing skills to chemists using Python, Jupyter notebooks, and the other Python packages. This text makes use of a variety of pac...
🐳 Проектная деятельность. Здесь хранятся лекции, практические задания и проекты с karpov_courses. Ссылка: https://karpov.courses/
IBM Data Science Professional Certificate
splearn: package for signal processing and machine learning with Python. Contains tutorials on understanding and applying signal processing.
A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python
本项目以应用为主出发，结合了从基础的机器学习、深度学习到目标检测以及目前最新的大模型，采用目前成熟的 第三方库、开源预训练模型以及相关论文的最新技术，目的是记录学习的过程同时也进行分享以供更多人可以直接进行使用。
Some python workbooks with various topics from Computational Physics
