Science & Lineal Algebra
Linear Algebra (Matrix), Determinant, Inverse, CoFactor, Adjoint, Scalar Multiplication, Subtraction, Plus, Multiplication, Transpose, Random, Trace and Identity.
Applications: Data Science, Data Analysis, Algorithms, Statistics, Engineering, Calculus, modeling, computing, fuzzy logic, others.
Coming soon Science, 2024
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Regression
To perform preliminary data analysis and predict future trends and areas such as medicine, engineering, data science, data analysis using Linear Regression.
Applications: Linear convertion, Drug response, Stock prices.
Algorithms: Simple Linear Regression, Multiple Linear Regression, Logistic Regression, Polynomial Regression.
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Classification
Identifying and classification which category an object belongs to.
Applications: Spam detection, image recognition.
Algorithms: KDTree, KDependent Bayes, Cluster Evaluation, Cross Validation, Native Bayes, SVM, Optiming SVM and Random Forest.
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Clustering
Automatic grouping of similar objects into sets.
Cluster analysis, also known as clustering, is a method of data mining that groups similar data points together.
K-means is a clustering method, which aims to partition a set of n observations into k groups in which each observation belongs to the group whose mean value is closest. It is a method used in data mining.
Applications: Customer segmentation, Grouping experiment outcomes
Algorithms: k-Means, Cluster evaluation, KNearest Neightbors.
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Neural Networks
A neural network is a method of artificial intelligence that teaches computers to process data in a way that is inspired by the way the human brain does.
Applications: Data processing and modeling: Validation, aggregation and data analysis. Design and finding faults in complex software systems. Control engineering: Monitoring of computer systems and manipulation of robots. Including the creation of autonomous systems and robots.
Algorithms: MultiLayer Back Propagation, Feed Forward, Genetic Algorithm, Adaline, BAM, HopField, Perceptron, RBF, Resilient Propagation, Nomalization Data and Import Models.
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Natural Language Processing
Natural language processing (NLP) refers to the branch of computer science—and more specifically, the branch of artificial intelligence or AI—concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.
These technologies enable computers to process human language in the form of text or voice data and to ‘understand’ its full meaning, complete with the speaker or writer’s intent and sentiment.
Applications: Spam detection, text translation, conversation assistants, voice synthesis.
Algorithms: NER, Sentence Detector, Sentiment Detector, Tokenizer.
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Image Processing and CV
Image processing is the set of techniques that are applied to digital images with the aim of improving quality or facilitating the search for information.
Computer Vision is a scientific discipline that includes methods to acquire, process, analyze and understand images of the real world in order to produce numerical or symbolic information so that they can be processed by a computer. Just as humans use our eyes and brains to understand the world around us
Applications: Object detection, Image analysis, Counting objects in an image.
Algorithms: Canny, Sobel, Gaussian, Median filter, Count Objects, Convert Color Image, Comparate images, Convert Binary, Mirror Image, Resize Image, Convert Gray, Sepia, White, Black, Features Image.
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Security
Using encryption processes applied to information security using symmetric and asymmetric keys.
Applications: Data encryption & decryption (data strings or files of any type).
Algorithms: AES, RSA, 3DES, SHA, SHA3, SHA256, SHA512, MD5, Base64, and Convert String to Binary.
PQC (Post Quantum Criptography) Coming soon 2024.
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Communications
Communications: Web Server, IP Forwarding (Give an IP so you can access your mobile from anywhere).
Applications: Remote access direct to any mobile device, table or PC, through a Web server.
Comunnications: Web Server, SSH, IP-Forwarding.
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