Author: www.big-data.tips

Caffe Deep Learning Framwork Protocol Buffers Prototxt Neural Network Model Machine Learning Algorithms Classification Clustering Regression Supervised Learning Unsupervised Tool

Caffe

Caffe is a deep learning framework that works well with big data. More general details about the Framework are given in our article on Caffe Deep Learning. This article describes a Caffe model and...

AutoKeras

AutoKeras is an open source Framework based on Keras to enable Neural Architecture Search (NAS) for deep learning architectures trained on big data. NAS is a technique to support the human design for neural...

Snake Make Snakemake Workflow Management Tool Workflow Engine Data Analysis Bioinformatics Python Reproducibility Scalability Portability Cloud Grid Cluster

Snake Make

Snake Make is a workflow management system used for reproducible and scalable big data analysis. It is often used in bioinformatics, but can be used also in other application areas. It is a user-friendly...

Precision Medicine Benefits

Precision medicine benefits are possible when medical decisions are based on of individual patients. The fundamental idea of this data-driven medical approach is described in our article on precision medicine. This article lists six...

Precision Medicine Stratified Medicine P4 Medicine Personalized Medicine Molecular Biomarkers Behavioral Biomarkers Patients Medical Decisions Predictive

Precision Medicine

Precision medicine is a data-driven medical approach that bases medicial decisions on invididual patients by using and individual patient characteristics. The approach is also called stratified medcine or personalized medicine. Some also call it...

Biomarkers Stratisfy Patients Measurable Quantity of Data Genomic alterations Molecular Markers Behavioral Disease Severity Scores Lifestyle Characteristics

Biomarkers

Biomarkers stand for any measurable quantity of big data or score that is used to stratify patients. In other words, stratifying patients mean in this context to arrange or classify them into well-defined risk...

Autoencoder Deep Learning Encoder Decoder Architecture Dimensionality Reduction Technique Unsupervised Learning Denoising Autoencoder High Dimensions

Autoencoder

Autoencoder refers to an unsupervised learning technique that is often used in the context of dimensionality reduction of big data. It projects some data from a higher dimension to a lower dimension via linear...

Euler Equation Fluid Dynamics Eulerian Functions Materials Fluids Liquids Velocity Pressure Density Kinematic Viscosity External Forces Navier-Stokes Model

Euler Equation

Euler equation refers actually to a set of equations named after Leonhard Euler. These equations are used in physical sciences in the field of fluid dynamics. They are also known as Eulerian functions of...

Dimensionality Reduction Techniques Convolutional Neural Network Principle Component Analysis PCA CNN Deep Learning Machine Learning Methods Algorithms

Dimensionality Reduction Techniques

Dimensionality reduction techniques are methods to reduce the dimensionality of a modeling problem. This is very important when working with big data and high-dimensional data sets. Learning from this data is a very challenging...