TPOT is a Python Automated Machine Learning tool
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning (AutoML) tool that optimizes machine learning pipelines using genetic programming.
Ciencia de Datos | š¬š§ Data Science
AutoML: a introduction tutorial about H2O Driverless AI
“H2O has been the driver for building models at scale. We are talking about billions of claims. You canāt do this with standard off the shelf open source techniques”. (H2o.ai).
Python for Everybody: Exploring Data in Python 3
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet. (Dr. Charles R. Severance)
La era de los datos | š¬š§ The Age of Data
La era de los datos | š¬š§ The Age of Data
“Diecinueve grandes expertos de todo el mundo esbozan las reformas ambiciosas y radicales necesarias para encarar los desafĆos de la era de los datos”. | š¬š§ “Nineteen leading experts from all over the world outline the major, radical reforms needed to address the challenges of the Age of Data”. (OpenMind. BBVA).
Python Data Science Handbook (Essential Tools for Working with Data)
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allāIPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
CĆ©lulas y proteĆnas: el modelo SNARE-CNN (red neuronal convolucional 2D)
Usando el modelo, en sus conclusiones, los autores seƱalan que las nuevas proteĆnas SNARE pueden identificarse con precisiĆ³n y usarse para el desarrollo de fĆ”rmacos. Y tratĆ”ndose de enfermedades como las neurodegenerativas, mentales y el cĆ”ncer podemos y debemos interesarnos por este trabajo aplicado al campo de la bioinformĆ”tica computacional, la minerĆa de datos y el Machine Learning.
