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Jose A Dianes
Data Analytics & Visualisation - SW Engineer PhD
Sessions / Jobs
For every 15 minutes
With more than a decade of experience, I have been involved in different aspects of Data Analytics and Enterprise Software applied to domains such as Life Sciences, Ambient Sensing, and Real-time Simulators. I am available for consulting (off-line) data science jobs, including effective data visualisations, statistical inference, prediction, classification, results communication and report. I regularly use R, Apache Spark, and cloud resources if needed.
- 5 years experience
I came to R by chance, while working in a bioinformatics institution. We needed to provide tools for researchers to deal with biological data. I have to confess that at first I didn't like it. Being a software engineer I prefer languages that allow you to build and scale complex software systems. R is not meant to be that way. The language is build for statistics and data analysis work, and has probably the richest ecosystem for that purpose. In the end I loved to work in RStudio and using DataFrames, ggplot2, and build all sort of machine learning models with just a few lines of code. Very powerful tool that you can now even combine with Apache Spark!
- 4 years experience
- 2 years experience
I came to Spark from a software engineering background. We had a Hadoop pipeline for clustering proteomics spectral data. Lately I've been working on on-line spectral search and on several Spark tutorials.
- 5 years experience
I came to machine learning and data analysis from a Software Engineering background. I have a PhD in real-time distributed systems and my interest is to build data products that give companies the edge. I am particularly interested in building data products that can scale to large amounts of data and work in real-time.
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset
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POSTS BY JOSE
Building a Movie Recommendation Service with Apache Spark & Flask - Part 2
This Apache Spark tutorial goes into detail on how to use Spark machine learning models, or even another kind of data analytics objects, within a web service. By using the Python language, we make this task very easy, thanks to Spark own Python capabilities and to Python-based frameworks such as Flask.
Data Science with Python & R: Dimensionality Reduction and Clustering
An important step in data analysis is data exploration and representation. In this tutorial we will see how by combining a technique called Principal Component Analysis (PCA) together with Cluster, we can represent in a two-dimensional space data defined in a higher dimensional one while, at the same time, be able to group this data in similar groups or clusters and find hidden relationships in our data.
Could've been better
Jose is very knowledgeable and patient. He helped me with my R code. He has excellent pedagogical qualities. I will definitely work with him again.
Jan 12, 2018
Jose is professional and offered creative and knowledgeable insights to help with my programming investigation using R, as well as being a very friendly and willing to help guy as a whole.
Jan 11, 2018
Jose is a talented programmer who provides expert guidance. He is patient with answering questions, and provides useful and efficient suggestions. I highly recommend working with him.
Dec 17, 2017
Jose can answer your questions in a timely manner and provides very great instruction. Clean and easy-to-understand codes. highly recommend! Great work. Very helpful.
Dec 9, 2017
Dec 8, 2017
Excellent help with tackling an asp site scraping questions! Addressed the problem completely with clear explanation.
Dec 5, 2017
Jose used a unique style to debug a raw data issue (even though I messaged thinking it was a ggplot issue) ,was quick in discovering it and provided a clear explanation using both visuals and text.
Dec 5, 2017
He helps in a short time. He prepares the session in advance, All my doubts were solved.
Aug 17, 2015
Very helpful!! He answer and solve my doubts very quick
Aug 17, 2015