196 skills found · Page 7 of 7
LRLVEC / IsingMonteCarloA numerical method to compute Ising model, accelerated by CUDA
meantrix / CorrpCompute multiple types of correlations analysis (Pearson correlation, R^2 coefficient of linear regression, Cramer's V measure of association, Distance Correlation,The Maximal Information Coefficient, Uncertainty coefficient and Predictive Power Score) in large dataframes with mixed columns classes(integer, numeric, factor and character) in parallel backend.
VadimAnIsaev / Library Of Numerical Analysis MSULibrary of Numerical Analysis of the Research Computing Center of the Moscow State University. Translation of subroutines into modern Fortran.
maddmhep / MaddmMadDM is a numerical tool designed to compute dark matter relic abundance, dark matter nucleus scattering rates, and dark matter indirect detection predictions in a generic model. Based on the existing MadGraph 5 architecture, MadDM is easily integrable into any MadGraph collider study.
ansi-code / NumtsNumTs is a TypeScript library that provides a set of mathematical functions and data structures that aim to reproduce some of the functionalities of NumPy, a popular Python library for numerical computing. NumTs is designed for developers who work with TypeScript and want to perform numerical operations efficiently.
yriyazi / Neural Network Implementation From Scratch Using NumPyThis repository contains an implementation of a neural network from scratch using only NumPy, a fundamental library for numerical computing in Python. The neural network is designed to perform tasks such as classification, regression, or any other supervised learning problem.
amit21AIT / Artifitial Neural Network Churn ModelingBusiness Problem: Dataset of a bank with 10,000 customers measured lots of attributes of the customer and is seeing unusual churn rates at a high rate. Want to understand what the problem is, address the problem, and give them insights. 10,000 is a sample, millions of customer across Europe. Took a sample of 10,000 measured six months ago lots of factors (name, credit score, grography, age, tenure, balance, numOfProducts, credit card, active member, estimated salary, exited, etc.). For these 10,000 randomly selected customers and track which stayed or left. Goal: create a geographic segmentation model to tell which of the customers are at highest risk of leaving. Valuable to any customer-oriented organisations. Geographic Segmentation Modeling can be applied to millions of scenarios, very valuable. (doesn't have to be for banks, churn rate, etc.). Same scenario works for (e.g. should this person get a loan or not? Should this be approved for credit => binary outcome, model, more likely to be reliable). Fradulant transactions (which is more likely to be fradulant) Binary outcome with lots of independent variables you can build a proper robust model to tell you which factors influence the outcome. alt text Problem: Classification problem with lots of independent variables (credit score, balance, number of products) and based on these variables we're predicting which of these customers will leave the bank. Artificial Neural Networks can do a terrific job with Classification problems and making those kind of predictions. Libraries used: Theano numerical computation library, very efficient for fast numerical computations based on Numpy syntax GPU is much more powerful than CPU, as there are many more cores and run more floating points calculations per second GPU is much more specialized for highly intensive computing tasks and parallel computations, exactly for the case for neural networks When we're forward propogating the activations of the different neurons in the neural network thanks to the activation function well that involves parallel computations When errors are backpropagated to the neural networks that again involves parallel computation GPU is a much better choice for deep neural network than CPU - simple neural networks, CPU is sufficient Created by Machine Learning group at the Univeristy of Montreal Tensorflow Another numerical computation library that runs very fast computations that can run on your CPU or GPU Google Brain, Apache 2.0 license Theano & Tensorflow are used primarily for research and development in the deep learning field Deep Learning neural network from scratch, use the above Great for inventing new deep learning neural networks, deep learning models, lots of line of code Keras Wrapper for Theano + Tensorflow Amazing library to build deep neural networks in a few lines of code Very powerful deep neural networks in few lines of code based on Theano and Tensorflow Sci-kit Learn (Machine Learning models), Keras (Deep Learning models) Installing Theano, Tensorflow in three steps with Anaconda installed: $ pip install theano $ pip install tensorflow $ pip install keras $ conda update --all
sanusanth / Java All Basic Program Part 2What is Java? Java is a popular programming language, created in 1995. It is owned by Oracle, and more than 3 billion devices run Java. It is used for: Mobile applications (specially Android apps) Desktop applications Web applications Web servers and application servers Games Database connection And much, much more! Why Use Java? Java works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc.) It is one of the most popular programming language in the world It is easy to learn and simple to use It is open-source and free It is secure, fast and powerful It has a huge community support (tens of millions of developers) Java is an object oriented language which gives a clear structure to programs and allows code to be reused, lowering development costs As Java is close to C++ and C#, it makes it easy for programmers to switch to Java or vice versa Setup for Windows To install Java on Windows: Go to "System Properties" (Can be found on Control Panel > System and Security > System > Advanced System Settings) Click on the "Environment variables" button under the "Advanced" tab Then, select the "Path" variable in System variables and click on the "Edit" button Click on the "New" button and add the path where Java is installed, followed by \bin. By default, Java is installed in C:\Program Files\Java\jdk-11.0.1 (If nothing else was specified when you installed it). In that case, You will have to add a new path with: C:\Program Files\Java\jdk-11.0.1\bin Then, click "OK", and save the settings At last, open Command Prompt (cmd.exe) and type java -version to see if Java is running on your machine Keyword Description abstract A non-access modifier. Used for classes and methods: An abstract class cannot be used to create objects (to access it, it must be inherited from another class). An abstract method can only be used in an abstract class, and it does not have a body. The body is provided by the subclass (inherited from) assert For debugging boolean A data type that can only store true and false values break Breaks out of a loop or a switch block byte A data type that can store whole numbers from -128 and 127 case Marks a block of code in switch statements catch Catches exceptions generated by try statements char A data type that is used to store a single character class Defines a class continue Continues to the next iteration of a loop const Defines a constant. Not in use - use final instead default Specifies the default block of code in a switch statement do Used together with while to create a do-while loop double A data type that can store whole numbers from 1.7e−308 to 1.7e+308 else Used in conditional statements enum Declares an enumerated (unchangeable) type exports Exports a package with a module. New in Java 9 extends Extends a class (indicates that a class is inherited from another class) final A non-access modifier used for classes, attributes and methods, which makes them non-changeable (impossible to inherit or override) finally Used with exceptions, a block of code that will be executed no matter if there is an exception or not float A data type that can store whole numbers from 3.4e−038 to 3.4e+038 for Create a for loop goto Not in use, and has no function if Makes a conditional statement implements Implements an interface import Used to import a package, class or interface instanceof Checks whether an object is an instance of a specific class or an interface int A data type that can store whole numbers from -2147483648 to 2147483647 interface Used to declare a special type of class that only contains abstract methods long A data type that can store whole numbers from -9223372036854775808 to 9223372036854775808 module Declares a module. New in Java 9 native Specifies that a method is not implemented in the same Java source file (but in another language) new Creates new objects package Declares a package private An access modifier used for attributes, methods and constructors, making them only accessible within the declared class protected An access modifier used for attributes, methods and constructors, making them accessible in the same package and subclasses public An access modifier used for classes, attributes, methods and constructors, making them accessible by any other class requires Specifies required libraries inside a module. New in Java 9 return Finished the execution of a method, and can be used to return a value from a method short A data type that can store whole numbers from -32768 to 32767 static A non-access modifier used for methods and attributes. Static methods/attributes can be accessed without creating an object of a class strictfp Restrict the precision and rounding of floating point calculations super Refers to superclass (parent) objects switch Selects one of many code blocks to be executed synchronized A non-access modifier, which specifies that methods can only be accessed by one thread at a time this Refers to the current object in a method or constructor throw Creates a custom error throws Indicates what exceptions may be thrown by a method transient A non-accesss modifier, which specifies that an attribute is not part of an object's persistent state try Creates a try...catch statement var Declares a variable. New in Java 10 void Specifies that a method should not have a return value volatile Indicates that an attribute is not cached thread-locally, and is always read from the "main memory" while Creates a while loop Method Description Return Type charAt() Returns the character at the specified index (position) char codePointAt() Returns the Unicode of the character at the specified index int codePointBefore() Returns the Unicode of the character before the specified index int codePointCount() Returns the Unicode in the specified text range of this String int compareTo() Compares two strings lexicographically int compareToIgnoreCase() Compares two strings lexicographically, ignoring case differences int concat() Appends a string to the end of another string String contains() Checks whether a string contains a sequence of characters boolean contentEquals() Checks whether a string contains the exact same sequence of characters of the specified CharSequence or StringBuffer boolean copyValueOf() Returns a String that represents the characters of the character array String endsWith() Checks whether a string ends with the specified character(s) boolean equals() Compares two strings. Returns true if the strings are equal, and false if not boolean equalsIgnoreCase() Compares two strings, ignoring case considerations boolean format() Returns a formatted string using the specified locale, format string, and arguments String getBytes() Encodes this String into a sequence of bytes using the named charset, storing the result into a new byte array byte[] getChars() Copies characters from a string to an array of chars void hashCode() Returns the hash code of a string int indexOf() Returns the position of the first found occurrence of specified characters in a string int intern() Returns the index within this string of the first occurrence of the specified character, starting the search at the specified index String isEmpty() Checks whether a string is empty or not boolean lastIndexOf() Returns the position of the last found occurrence of specified characters in a string int length() Returns the length of a specified string int matches() Searches a string for a match against a regular expression, and returns the matches boolean offsetByCodePoints() Returns the index within this String that is offset from the given index by codePointOffset code points int regionMatches() Tests if two string regions are equal boolean replace() Searches a string for a specified value, and returns a new string where the specified values are replaced String replaceFirst() Replaces the first occurrence of a substring that matches the given regular expression with the given replacement String replaceAll() Replaces each substring of this string that matches the given regular expression with the given replacement String split() Splits a string into an array of substrings String[] startsWith() Checks whether a string starts with specified characters boolean subSequence() Returns a new character sequence that is a subsequence of this sequence CharSequence substring() Extracts the characters from a string, beginning at a specified start position, and through the specified number of character String toCharArray() Converts this string to a new character array char[] toLowerCase() Converts a string to lower case letters String toString() Returns the value of a String object String toUpperCase() Converts a string to upper case letters String trim() Removes whitespace from both ends of a string String valueOf() Returns the primitive value of a String object String Method Description Return Type abs(x) Returns the absolute value of x double|float|int|long acos(x) Returns the arccosine of x, in radians double asin(x) Returns the arcsine of x, in radians double atan(x) Returns the arctangent of x as a numeric value between -PI/2 and PI/2 radians double atan2(y,x) Returns the angle theta from the conversion of rectangular coordinates (x, y) to polar coordinates (r, theta). double cbrt(x) Returns the cube root of x double ceil(x) Returns the value of x rounded up to its nearest integer double copySign(x, y) Returns the first floating point x with the sign of the second floating point y double cos(x) Returns the cosine of x (x is in radians) double cosh(x) Returns the hyperbolic cosine of a double value double exp(x) Returns the value of Ex double expm1(x) Returns ex -1 double floor(x) Returns the value of x rounded down to its nearest integer double getExponent(x) Returns the unbiased exponent used in x int hypot(x, y) Returns sqrt(x2 +y2) without intermediate overflow or underflow double IEEEremainder(x, y) Computes the remainder operation on x and y as prescribed by the IEEE 754 standard double log(x) Returns the natural logarithm (base E) of x double log10(x) Returns the base 10 logarithm of x double log1p(x) Returns the natural logarithm (base E) of the sum of x and 1 double max(x, y) Returns the number with the highest value double|float|int|long min(x, y) Returns the number with the lowest value double|float|int|long nextAfter(x, y) Returns the floating point number adjacent to x in the direction of y double|float nextUp(x) Returns the floating point value adjacent to x in the direction of positive infinity double|float pow(x, y) Returns the value of x to the power of y double random() Returns a random number between 0 and 1 double round(x) Returns the value of x rounded to its nearest integer int rint() Returns the double value that is closest to x and equal to a mathematical integer double signum(x) Returns the sign of x double sin(x) Returns the sine of x (x is in radians) double sinh(x) Returns the hyperbolic sine of a double value double sqrt(x) Returns the square root of x double tan(x) Returns the tangent of an angle double tanh(x) Returns the hyperbolic tangent of a double value double toDegrees(x) Converts an angle measured in radians to an approx. equivalent angle measured in degrees double toRadians(x) Converts an angle measured in degrees to an approx. angle measured in radians double ulp(x) Returns the size of the unit of least precision (ulp) of x double|float
LeonidSavtchenko / ArachneSoftware for the synthesis of realistic neural networks and their numerical processing on remote clusters using parallel computing
bhelmichparis / Laplace MinimaxRoutine that computes the numerical Laplace weights and exponents of orbital energy denominators using the minimax approximation
aurbano / SplineJSJavaScript library for numerical computing and plotting
sision0816 / ComputationalSolidMechanicsUse numerical method (Finite Element Method) compute the solid mechanics problems. From continuous mechanics theory, to , mesh, materials model, element assemble, displacement solver, static and dynamic solver
trixi-framework / Paper 2021 JuliaconAdaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
ViennaRNA / TreekinCompute folding dynamics on coarse grained version of an energy landscape by numeric integration of a Markov process
scijs / Quadratic RootsCompute the real roots of a quadratic equation in a numerically stable manner
anpar / EE WCC MapReduceSource code of the numerical experiments presented in "Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce" by Antoine Paris, Hamed Mirghasemi, Ivan Stupia and Luc Vandendorpe (presented at SPAWC19).
kapikantzari / Segmentation EvaluationCompute the performance metrics (dice coefficient, intersection over union, Matthew's correlation coefficient, accuracy, Hausdorff distance, sensitivity, precision, and F measure) between the computer segmentation results and radiologist segmentation results. Visualize the results on the original CT scan and export both numerical results and overlaid image files to a customized location.
CarlosMatHid / Variational Quantum Monte CarloThe goal of this project is to compute an upper bound to the ground state energy for different quantum systems: the Harmonic Oscillator, the Hydrogen atom and the Helium atom. To do so, we make use of the variational principle and the integrals are performed using the so called Quantum Monte Carlo method, for which we will need to implement the Metropolis algorithm. Finally, the numerical simulations will be compared to analytical (if possible) and experimental results for each case. The results show a perfect accordance with other literature and experimental values.
Ali-Zolfaghari / Lid Driven Cavity SIMPLEThe lid-driven cavity is a well-known benchmark problem for viscous incompressible fluid flow. We are dealing with a square cavity consisting of three rigid walls with no-slip conditions and a lid moving with a tangential unit velocity. The lower left corner has a reference static pressure of 0. In computational fluid dynamics (CFD), the SIMPLE algorithm is a widely used numerical procedure to solve the Navier–Stokes equations. SIMPLE is an acronym for Semi-Implicit Method for Pressure Linked Equations. The algorithm is iterative. The basic steps in the solution update are as follows: Set the boundary conditions. Compute the gradients of velocity and pressure. Solve the discretized momentum equation to compute the intermediate velocity field. Compute the uncorrected mass fluxes at faces. Solve the pressure correction equation to produce cell values of the pressure correction. Update the pressure field: where urf is the under-relaxation factor for pressure. Update the boundary pressure corrections. Correct the face mass fluxes. Correct the cell velocities by the gradient of the pressure corrections and the vector of central coefficients for the discretized linear system representing the velocity equation and Vol is the cell volume. Update density due to pressure changes.
PacktPublishing / Fast Numerical Computing With PythonFast Numerical Computing with Python by Packt
