4 रिपॉजिटरी
Awesome GitHub RepositoriesInput Flatteners
Utilities for reshaping input tensors within model architectures to simplify training loop data handling.
Distinct from Model Capability Extensions: Focuses on tensor reshaping for model input compatibility, distinct from document flattening or UI input configuration.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Input Flatteners. Refine with filters or upvote what's useful.
Awesome Input Flatteners GitHub Repositories
AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
- mnielsen/neural-networks-and-deep-learning
mnielsen/neural-networks-and-deep-learning
17,721GitHub पर देखेंThis project is a comprehensive educational resource and curriculum designed to teach the mathematical foundations and practical implementation of neural networks. It provides a structured path for understanding how computers learn from data, covering core concepts such as gradient descent, backpropagation, and the biological inspiration behind artificial neurons. The platform distinguishes itself by combining theoretical proofs with hands-on implementation exercises. It demonstrates the universal approximation theorem through visual explanations and guides users in building various architect
Implements sigmoid activation functions to ensure predictable, incremental changes in network outputs.
Python - mathnet/mathnet-numerics
mathnet/mathnet-numerics
3,717GitHub पर देखेंThis project is a numerical computing library designed for scientific and engineering mathematical operations. It functions as a comprehensive linear algebra framework, a statistical analysis library, and a toolkit for mathematical optimization and numerical integration. The library is distinguished by its provider-based native acceleration, which allows managed code to be swapped for platform-native binary libraries to increase the performance of computationally intensive routines. It also supports a hybrid approach to matrix storage, implementing separate strategies for dense and sparse mat
Implements the sigmoid logistic function and its inverse for mapping inputs to a probability range.
C#csharpdifferentiationfft - hosseinmoein/dataframe
hosseinmoein/DataFrame
2,917GitHub पर देखेंDataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f
Calculates sigmoidal activation functions, including logistic, algebraic, and hyperbolic tangent variants across data columns.
C++aicppdata-analysis - towardsai/tutorials
towardsai/tutorials
1,023GitHub पर देखेंThis project is an educational collection of tutorials and executable code notebooks focused on data science, machine learning, deep learning, and natural language processing concepts in Python. It provides instructional resources covering statistical analysis, linear algebra, artificial intelligence algorithms, and step-by-step guides for developers learning data science. The repository covers a broad spectrum of computational and statistical capabilities, including neural network construction, gradient-based optimization techniques, curve fitting, regression modeling, and collaborative filt
Applies sigmoid activation functions to transform arbitrary output values into bounded ranges.
Jupyter Notebookcollaborative-filteringdata-sciencedeep-learning
