to do
Appunti
Ricerca e acquisto casa
La mia piccola esperienza
Proprietà delle operazioni
elementary school
Favorite quotes
my favorite phrases marked over the years
R: Bayesian Statistics
Turn the Bayesian Crank
Wereables
Smartbands and Smartwatch
Android Apps
useful tools
Browser configuration
Must have extensions and utilities
Windows 10: utilities
ho inserito anche alcuni siti molto utili
Ubuntu: software
must have.. for me
Ubuntu: commands
useful commands
Ubuntu: environment
improving it
Markdown
markdown tips
GitHub pages
how to
GNU Image Manipulation Program
GIMP: settings and learning
Data Science Pipeline
Let’s try to define a path
OpenProject
Project Management Software
Python: Amazon Web Services and Spark
Cloud Computing with Amazon
Python: TensorBoard
Machine Learning
Python: Neural Networks
Machine Learning – House Sales, Breast cancer and LendingClub dataset
Python: TensorFlow
TF locally and through Google Colab – CIFAR10 dataset
TensorFlow: setup
TF 2.2.0 on Ubuntu 18.04 with CUDA 10.1, cuDNN v7.6.5 and Nvidia 450
Python: Natural Language Processing
Machine Learning – Yelp Review dataset
Python: Recommender system
Machine Learning – MovieLens100K dataset
Python: Principal Component Analysis
Machine Learning
Python: K Means Clustering
Machine Learning – blob dataset, college dataset
Python: Support Vector Machine
Machine Learning – Breast cancer dataset and Iris dataset
Python: Tree and Random Forest
Machine Learning – Kyphosis dataset
Python: k-Nearest Neighbors
Machine Learning
Python: Logistic Regression
Machine Learning – Titanic dataset
Python: Linear Regression
Machine Learning – USAhousing dataset, Boston dataset
Machine Learning Theory
Some concepts and metrics
Python: two examples
Exploratory Data Analysis – 911 Calls and Finance datasets
Python: Plotly and Choropleth
Data Visualization – Covid19 dataset
Python: Plotly and Cufflinks
Data Visualization
Python: Seaborn
Data Visualization
Python: Matplotlib
Data Visualization
Python: Pandas
Data Analysis
Python: NumPy
Data Analysis
Python: the beginning
Jupyter Notebook, Conda Environments and Basic Python
R
something useful
Desktop configuration
(not expensive) build 04/2017