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Lines of code distribution across 11 owned repositories
I-Shaped Developer
I-shapedSpecialist — deep expertise in HTML
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Análisis predictivo de precios de autos. El proyecto se llevó a cabo en el lenguaje de programación R
Using water_potability.csv from Water Quality in Kaggle, in this project I intend to analyze the data and predict the quality of water (potability) based on the pH level, hardness, solids, chloramines, sulfate, conductivity, organic carbon, trihalomethanes, and turbidity. This project has the aim to fit different machine learning models to find the best one to predict if the water is safe to drink (1) or not (0).
Data repository for seaborn examples
In this project the aim was to analyze the MovieLens dataset and create a machine learning model that predicts movie ratings.
Organic waste project.
In this project I make a quick analysis of the real gross domestic product and real gross domestic product per capita in Mexico
Function that takes the DNA sequence and the enzyme recognition sequence (both 5' to 3'), and displays "The recognition sequence was not found" if the enzyme recognition sequence was not found in the DNA strand or displays the DNA sequence showcasing in lowercase letters the enzyme recognition sequence along with an answer TRUE or FALSE to confirm that the final answer is the same as the DNA sequence taken by the function, which should always be TRUE. Also, if the DNA sequence is shorter than the enzyme recognition sequence, the function returns an error.
In this mini-project I o import the DNA-coding-strand sequence of the gene Triakis scyllium IgNAR clone 3, which encodes for immunoglobulin NAR, and make the mRNA sequence out of it.
En este proyecto se comparan diferentes parámetros socioeconómicos entre un país de ingreso alto (como Canadá) y un país de ingreso bajo (como Bolivia). De esta manera se ven las diferencias
En este proyecto se analizó el desempleo en México desde diferentes perspectivas. Por ejemplo, por edad y por entidad federativa. Además, se analizó la TCCO para determinar las condiciones laborales. Todos los datos fueron recuperados del INEGI y fueron depurados para que tuvieran un formato adecuado para el análisis.
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