Camilo Diaz Salinas Data Engineer • Data Scientist • Data Analyst

About Me Projects Blog

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Camilo Diaz Salinas

Data Engineer • Data Scientist • Data Analyst • Azure • AWS • Electronic Engineer
I always keep in constant learning and evolution
When there's a will there's a way ⛩️

Profile

I'm a Data Engineer with proven skills in solving technological challenges for startups and companies across various sectors, emphasizing my ability to transform data into actionable insights and improve operational efficiency. I specialize in implementing powerful solutions that leverage ML, NLP, cloud computing, and Big Data. I've achieved significant improvements in productivity and competitiveness for the companies I've collaborated with. Additionally, I have a strong track record of contributions to open-source projects, reflecting my commitment to the tech community and my passion for continuous learning.
In my free time I enjoy experimenting (a.k.a. breaking stuff) in Linux operative systems. When I get tired of technology and those kinds of topics, I like to paint and read philosophy.

📢 Ask me whatever you want!. I'm interested in helping and sharing.

Tech Stack

Development

Machine Learning

Data

SQL & NoSQL

Deep Learning

Deployment & Infrastructure

Version Control

Featured Projects

Adversary Attack
ECODATA: E-Commerce Olist Analysis
  • Python: 3.9, TensorFlow(tf): 2.9.1, TensorFlow Keras(models, layers): 2.9.1, matplotlib, pyplot(plt): 3.6.2, numpy(np): 1.23.1, pandas(pd): 1.5.2, Plotly Express: 1.9.0, Scikit-learn, Power BI, MySQL

We carried out this project together with the aim of performing ETL, EDA, transaction prediction, and customer segmentation for an e-commerce platform.

See Repository
Platzigram_Django
Scalable ETL Pipeline with MySQL, FastAPI, and Docker for Multimedia Streaming Data
  • Python: 3.9, FastAPI, os, json: 3.7.4, pandas(pd): 1.5.2, numpy(np): 1.23.1, re, chardet, pathlib, sqlalchemy, MySQL, Docker, Conda

Development of a scalable ETL pipeline using MySQL, FastAPI, and Docker to process, store, and expose data from streaming platforms. This project optimizes the data flow, enabling efficient queries and providing dynamic endpoints for real-time analysis.

See Repository
Adversary Attack
Fruit Infection Disease
  • Python: 3.9, TensorFlow(tf): 2.9.1, TensorFlow Keras(models, layers): 2.9.1, ImageDataGenerator(preprocessing.image): 2.4.0, ModelCheckpoint(callbacks): 2.9.1, matplotlib, pyplot(plt): 3.6.2, os, gc, l1_l2(regularizers): 2.9.1, InceptionV3(applications.inception_v3): 2.9.1, TensorBoard(callbacks): 2.9.1, numpy(np): 1.23.1, preprocessing(image): 2.4.0

Disease classifier in strawberries, tomatoes, and beans using Computer Vision with TensorFlow and Keras.

See Repository
Platzigram_Django
Object Detection - Marine Animals
  • Python: 3.9, os, zipfile: 3.10, random, shutil: 3.10, json: 3.7.4, pickle: 5.0.0, pandas(pd): 1.5.2, tensorflow(tf): 2.9.1, sys, PIL(Image): 9.1.0, object_detection.utils: 0.1.0, collections(namedtuple, OrderedDict), object_detection.utils: 0.1.0, object_detection.protos: 0.1.0, google.protobuf: 3.20.1

This project aims to use artificial intelligence-based object detection technology to contribute to the conservation and preservation of manta rays, sharks, and sea turtles in the Caribbean Sea.

See Repository
Adversary Attack
Amazon reviews - Sentiment-algorithms
  • Python: 3.9, google.colab, sklearn.feature_extraction.text.TfidfVectorizer: 1.1.3, sklearn.feature_selection.SelectKBest, chi2: 1.1.3, sklearn.model_selection.train_test_split: 1.1.3, sklearn.linear_model.LogisticRegression: 1.1.3, sklearn.ensemble.RandomForestClassifier: 1.1.3, sklearn.naive_bayes: 1.1.3, sklearn.metrics.confusion_matrix: 1.1.3, seaborn(sns): 0.14.1, numpy(np): 1.23.5, nltk: 3.8 nltk.corpus.stopwords

Sentiment model with NLP classifying books reviews on Amazon from 1 to 5.

See Repository
WebLinearRegresion
Color Detection - Backpropagation-MLP
  • Java(JDK,JRE,Java Standard Library): 11(LTS), Apache Commons IO: 2.12.1, StringTokenizer, BufferedReader, PrintWriter

With the backpropagation of the neural network, it is planned to be used for yellow color detection. Completely programmed in Java.

See Repository
Wardo Ecommerce
Fuzzy-PD-controller
  • Webots: R2019b, Java: 11(LTS), Webots Java API: R2019b, Fuzzy PD controller(own implementation)

A fuzzy PD Controller for a pre-designed arm in Webots R2019b.

See Repository
CMS with rails
Analysis Of World Population Dataset 🌎
  • Python: 3.9, Pandas: 1.5.2, NumPy: 1.23.1, Seaborn: 0.12.1, Plotly Express: 1.9.0, Matplotlib: 3.6.2

The data is from US Census Bureau. We are given the population of every countries from years 1970,1980,1990,2000,2010,2015,2020 and 2022.

See Repository
Notevares_apk
Playlist_Simulator
  • Python: 3.9, random: 3.9, queueList(PlayList)

A simulator of a music playlist was created which applies the use of Queue based on Nodes.

See Repository