We found 8 results that contain "algorithms"

Genetic algorithms are unique ways to solve complex problems by harnessing the power of nature. By applying these methods to predicting security prices, traders can optimize trading rules by identifying the best values to use for each parameter for given security.

Dynamic time warping is an algorithm for measuring similarity between two sequences that may vary in time or speed. For instance, similarities in walking patterns would be detected, even if in one video the person was walking slowly and if in another he or she were walking more quickly, or even if there were accelerations and deceleration during the course of one observation. DTW has been applied to video, audio, and graphics – indeed, any data that can be turned into a linear representation can be analyzed with DTW.

Digital image processing deals with manipulation of digital images through a digital computer. It is a subfield of signals and systems but focus particularly on images. DIP focuses on developing a computer system that is able to perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms, and gives an image as an output. The most common example is Adobe Photoshop. It is one of the widely used application for processing digital images

Reinforcement Learning
Reinforcement learning is a subfield of machine learning in which systems are trained by receiving virtual "rewards" or "punishments," essentially learning by trial and error. Google's DeepMind has used reinforcement learning to beat a human champion in the Go games. Reinforcement learning is also used in video games to improve the gaming experience by providing smarter bot.

One of the most famous algorithms are:

Q-learning
Deep Q network
State-Action-Reward-State-Action (SARSA)
Deep Deterministic Policy Gradient (DDPG)

Data Science is a process of extracting, manipulating, visualizing, maintaining data as well as generating predictions.
A Data Scientist is supposed to have knowledge of various data operations as well as machine learning algorithms. Using Data Science, industries are able to extract insights and forecast their performance.

Data Science is a field that makes use of scientific methods and algorithms in order to extract knowledge and discover insights from data (structured on unstructured). Data Analytics is the process of using specialized systems and software to inspect information in datasets in order to derive conclusions

Computer science is the study of algorithmic processes, computational machines and computation itself.[1] As a discipline, computer science spans a range of topics from theoretical studies of algorithms, computation and information to the practical issues of implementing computational systems in hardware and software

The tools of business intelligence are also limited to the analysis of management information and curation of business strategies. However, the tools of a data scientist involve complex algorithmic models, data processing, and even big data tools. While BI focuses on generating reports based on the internal structured data, Data Science focuses on generating insights out of the data.