Jerald Espinoza Flores's repositories
Pytorch-fundamentals
Text classification model with Pytorch
Census_income_classification
Decision Tree and Random Forest model.
Decision-tree-and-random-forest-fundamentals
Decision Trees and Random Forests are powerful machine learning techniques that are widely used in a variety of fields, including finance, healthcare, marketing, and more. In this text, we will explore the basics of decision trees and random forests, how they work, and their applications in machine learning.
Linear-Algebra-for-ML-and-PCA
Linear algebra is a branch of mathematics that focuses on the study of systems of linear equations and the geometry of vector space. In the field of machine learning, linear algebra is used to analyze and manipulate large data sets and to create predictive models.
Bubble-Selection-Sort-Algorithms
Sorting algorithms are very important in technology because they allow programmers and data scientists to process large amounts of information in reasonable time, which is essential in fields such as data analysis, artificial intelligence, and machine learning.
Linear-Algebra-Fundamentals
Linear Algebra is a branch of mathematics that focuses on the study of vectors, matrices, and systems of linear equations. This discipline has numerous uses in technology, including artificial intelligence, machine learning, computer vision, cryptography, simulation, and optimization.
Inferencial-statistic-basic-tools
Inferential statistics is a branch of statistics that focuses on drawing conclusions about a population from a sample. In the context of machine learning, inferential statistics is an essential tool for evaluating the validity of machine learning models and for making decisions based on the results of these models.
Customer-Segmentation-Clustering
In this project, unsupervised clustering was performed. Using dimensionality reduction followed by agglomerative clustering. 4 groups were used to profile clients according to their family structures and income/expenses. This can be used in planning better marketing strategies.
Clustering-Scikit-learn
In this repository we work with various basic examples of how data clustering is done with the help of Scikit-learn. This will help us to work with future projects.
Logistic-regression
In this repository we make an introductory example of how to carry out a logistic regression in order to give us an idea for future projects that we will carry out..
Demo-with-Gradio-Hugging-Face
In this repository we collect the code used in building Demos for our Hugging Face platform. Where we carried out a project of voice recognition and transformation to text with Gradio. Resulting in an interface and a simple but very useful design for the consumption of our model. Learn more about my Demos and Spaces at
Models-HuggingFace
In this repository we collect the code used to build models for our Hugging Face platform. Where we carried out two different computer vision and text classification projects.
Neurals-Network-Build
In this repository we archive the construction of some examples of simple neural networks as fundamental examples for later more robust constructions.
DB-metro_cdmx-MySQL-MariaDB
We built a database as a project to be able to organize and manage the train stations in Mexico City. We divide the records into train lines, stations, locations, drivers and relate them to each other.
Computer-Vision-Smart-City-TF
In this computerized vision project with Tensor Flow, we made a counter for vehicles in transit, classifying them between cars and motorcycles to measure traffic on highways. The purpose is to be able to implement this learning model in a smart city and have better control by the municipalities.