Spiega documentation

Article: spiega

What spiega is about

spiega tech
shared documentation across projects

spiega tech

Spiega is a collection of articles/post written during 17y of career spanning over 3k3 source code files and 2k images. The main areas are around data science and the impact of using machine learning in operations and business. Some content is presented as slides or as automated generated summary in the overview page. For a more business oriented description of those activities refer to spiega business.

module_library.png

Figure 1: module library

During this time I tried to make the organize the diverse topics into some main areas which are:

management and client projects   management

<2013-09-12 Thu>

Here is a collection of experiences regarding project scoping, execution and reporting

governance
manage and design data platforms
team management
how to manage and kick off a team
project tools
what makes the execution of a project efficient

AncillarySketch.png

Figure 2: module library

consultancy and service provider   consultancy

<2013-06-03 Mon>

dauvi
ERP tools and firm consultancy, mainly focused on setting up and implementing ERP tools and connecting different company components
intertino
web services. Offer segmentation strategies, agent compensation models, lagged metrics, customer lifetime value calculation, contact channels main and control metrics, scooter movement analysis, auto sensors assessment, shared bike usage evaluation, and weather prediction models.

Comment.png

Figure 3: module library

optimization experience   data_science

<2017-10-04 Wed>

Collection of projects for optimization challenges

geomadi
articles on geo features, routing applications, location intelligence, motorway stoppers analysis, routing comparisons, and sensor triangulation.
antani
optimization engine (reinforcement learning, simulations).
mallink
simulation engine in python.
allink
C/C++ simulation code for biophysical membranes

doc_lib.svg

Figure 4: module library

data science competences   data_science

<2014-11-03 Mon>

Collection of libraries used as support to data projects

kotoba
generative ML. ML painting, text generation, music composition, agent naming environment for redundancy in images.
albio
time series analysis.
lernia
machine learning library used across multiple projects. Regressions without neural networks
deep lernia
machine learning library used across multiple projects. Neural network models
ndoe
Equations of motion, ride behavior, mobility concepts, POI capture rate, activation potential, data quality assessment, telemetry data types, prediction anomalies, and spatial analysis.

motion_pattern.svg

Figure 5: data science competences

programming and devops   dev

<2013-05-04 Sat>

Collection of work to develops products and manage data platforms

sawmill
big data processing. Data platform basics, data storage applications, compliance with access rules for sensitive data, modeling concepts, security practices, webserver and networking principles, messaging systems, middleware to protect requests, cloud provider impressions, CI/CD processes, testing methods, scheduling jobs, log processing, UI and data visualization techniques, and programming documentation.
intertino
web services. Offer segmentation strategies, agent compensation models, lagged metrics, customer lifetime value calculation, contact channels main and control metrics, scooter movement analysis, auto sensors assessment, shared bike usage evaluation, and weather prediction models.
malastro
useful scripts to manage a laptop, a server, embedded devices, media… Mainly using bash, ffmpeg…

data_pipe1.png

Figure 6: data pipe example

art and science   science

<2002-10-03 Thu>

Non commercial projects around art, music and science

kotoba
generative ML. ML painting, text generation, music composition, agent naming environment for redundancy in images.
science
scientific contributions. PhD defense/paper on membrane inclusion objects, master defense/thesis on nanoparticle stability, bachelor defense/thesis on ion diffusion in lattice, Fokker-Planck equations, Fluttuazione theorem, physics papers, computer science lectures, PLOS One paper on influenza fusion, PR Letters paper on string method, and Sciencedirect paper on pore formation.
algorithmics
computer science features mainly used in scientific computation
viudi
music tech including theoretical discovery of composition, electronics.

PresProfBilayer.png

Figure 7: module library

hardware   dev

<1997-03-04 Tue>

sciame
IoT applications. Coil for pickups/sustainers, synth collection, DSP, effects, mechanical amplifier, no-keyboard keyboard (touch surface), MIDI router player, audio mixer with op amps, piezo buffer for impedance matching and noise reduction, and creative coding techniques including openCV, openFrameworks, and processing.

coiler.png

Figure 8: sciame library

management

This section collects the relevant experiences in project and team management. The whole list of the 40 projects is in portfolio.

regression_tree.png

Figure 9: management experience

project tools   management

<2026-02-04 Wed>

Being efficient in running projects is essential and (especially in an agentic world) we need to prepare a good background for those agents to operate

agent workflow
org files
productivity with org files
agent context
instruct agents how to behave and be productive
agentic interview
an interview run by agents
documentation present
knowledge graph
multimedia utils

InfraSketch.png

Figure 10: module library

governance   management

<2014-10-04 Sat>

Data platform management

26-2?] LLM governance
how to manage agentic systems
26-2?] storage governance
avoid resource waste in storing and processing data
13-2?] management
management experience
26-2?] data_sovereignty
on-prem infra
26-2?] knowledge_graph
auto generated locally

gantt.svg

Figure 11: module library

team management   management

Team management

13-2?] team composition
how to set up a team, SoW
13-2?] team productivity
what makes a team productive
13-2?] well being
body health for productivity

CustomerJourney.png

Figure 12: module library

optimization

Libraries mainly focused on optimization engine (operation, mobility…)

node_call.svg

Figure 13: module library

geomadi   data_science

<2017-10-16 Mon>

Geomadi was used to perform complex operations on a large network. The mongo database contained all the information regarding maps and POIs in Germany and we were analyzing spatial data regarding specific subset of a complex network. The library uses spatial queries and geometrical transformations.

17-19] graph creation
for routing applications
17-19] location intelligence
to enrich predictions
17-19] motorway stoppers
analysis on motorway traffic and capture rate
17-19] routing comparison
comparing routing solutions
17-19] triangulation of sensor data
locate mobile users
17-20] spatial utils
for GIS

cell_deformation.png

Figure 14: geomadi library

antani   data_science

<2019-10-16 Wed>

Antani is an optimization engine for logistics building efficient routes inspired by ants. The routes grow as polymers and variate to maximize opportunity/cost. This is a mixture of MonteCarlo as built in my PhD thesis and reinforcement learning. Each move has different polymer expansion options and the reinLearn decides what action to take to improve overall optimization time.

antani_frontend.png

Figure 15: antani library

mallink   data_science

<2019-10-16 Wed>

Mallink is the python adaptation of allink which was writte 2008-2012 in C++ and used as engine for antani

ndoe   data_science

<2017-10-16 Mon>

Ndoe analyzes motion behaviors and builds mobility reports

dens_traj3.png

Figure 17: ndoe motion patterns

data science

Machine learning and statistics used in different projects

feat_regularisation.png

Figure 18: module library

lernia   data_science

<2014-11-16 Sun>

Lernia is a library used across project to use ML. It divides into lernia and deep_lernia where the second one is built on keras

weather_feature.png

Figure 19: lernia library

albio   data_science

<2014-11-16 Sun>

Albio is a library to work with time series. During my career I used a lot of series decomposition and forecasts.

15-20] albio forecast
with exogen variables
15-20] time series
forecast in production

stat_prop.png

Figure 20: albio library

deep lernia   data_science

<2016-11-16 Wed>

Neuronal networks

result_order.png

Figure 21: deep lernia library

programming and devops

Knowledge used across the projects. How we take big logs and process them to get the most important information out of the big volume.

sawmill_log.jpg

Figure 22: sawmill library

sawmill   dev

<2013-11-16 Sat>

Big data, data engineering, data pipelines, machine learning ops

13-2?] data platform basics
example designs and principles
13-2?] data storage
applications and principles
14-2?] data compliance
access, sensitive data, anonymization, retention
15-2?] data modeling
concepts and applications
15-2?] security
practices and examples
12-2?] webserver and networking
for websites and traffic to containers
20-2?] messaging system
for stream and IoT
17-2?] middleware
to protect and speed up external requests
15-2?] cloud providers
impressions and experiences
15-2?] CI/CD
praxis and options
06-2?] test and checks
types and necessity
17-2?] scheduling jobs
monitor and plan batch processes
15-2?] log processing
from web, Iot, applications
06-2?] UI and data visualization
for the business and client’s insights
12-2?] admin tools
collection of script to admin a system

malastro   dev

<2006-11-16 Thu>

Development, sysadmin, prototyping

06-2?] programming praxis
documentation, conventions, processes
02-2?] emacs
mighty editor
06-13] c++
simulations, native visual applications, openGL
13-2?] python
data exploration, visualization, ETL
05-17] R
data exploration, visualization, ETL
22-2?] go
middelware to interact with relational databases
06-2?] SQL
manage databases, create tables, join, format
13-2?] app
native, angular, react, nodejs, cordova
06-2?] websites
html5, css, bootstrap, php
06-2?] javascript
openlayer, d3.js, maps
06-2?] node
bot, automation, server
17-20] spark
batch processing of logs

dev_log.jpg

Figure 23: malastro library

assessments   data_science

<2019-07-03 Wed>

Coding interviews

19] scooter movement
a portal for visualizing geo data
20] auto sensors
analyze connected cars data
19] shared bike usage
user usage of ride hail
17] ufo sightnings
geospatial information
2?] weather prediction
basics around data science

area_num.png

Figure 24: assessment library

consultancy and service provider

How to advice companies and clients to develop a digital/data strategy.

front_back.svg

Figure 25: management experience

intertino   consultancy

<2013-11-16 Sat>

Web marketing and digital services, customer retention and communication strategies

audPerformance.jpg

Figure 26: intertino library

dauvi   consultancy

<2013-11-16 Sat>

SME consultancy, ERP systems, digital strategies

dauvi
presentation of the projects

offgrid.svg

Figure 27: geomadi library

art and science

Non commercial projects for art and science

vec3d_2.png

Figure 28: art and science

kotoba   art

<1999-07-10 Sat>

Language and perception

19-2?] painting with ML
generative ai
17-2?] text generation
04-2?] music composition
23-2?] agent naming environment
11-12] redundancy in natural images
99-2?] phonosymbolic language
can we create a phonosymbolic language?

gen_cover.jpg

Figure 29: kotoba library

viudi   art

<2013-03-04 Mon>

Music development

13] entropy in music
how to recognize the author of a song
23] music chart valuation
how people judge the quality of songs
06] music composition
generative melody generator
10] video production
create songs with musical gears
10] video presentation
description of the channel
10] video detail
video detail

DistCanzoni.png

Figure 30: viudi library

allink   dev

<2008-09-15 Mon>

Software created during the PhD thesis

08-12] documentation
for the project allink in C++

science   science

<2002-09-30 Mon>

Documents during the physics research period

09-13] PhD defense
membrane inclusion objects
09-13] PhD thesis
membrane inclusion objects
08-09] master defense
nanoparticle stability
08-09] master thesis
nanoparticle stability
05-06] bachelor defense
ion diffusion in lattice
05-06] bachelor thesis
ion diffusion in lattice
11-11] Fokker-Plank
and master equations
07-07] Teorema della fluttuazione
traiettorie a entropia negativa
02-09] Fizikaj Eroj
klassika kaj kvuantuma mekaniko
13-13] Lezioni di informatica
per piccole imprese
12-12] Paper
Influenza Fusion, String method, Pore formation

fizikaj_eroj.png

Figure 32: fizikaj eroj library

algorithmics   dev

<2006-03-02 Thu>

Development of algorithms for better performances

NpConfBiasSketch.png

Figure 33: algo library

media   art

<2013-02-04 Mon>

Collection of media projects

13-15] creative coding
openCV, openFrameworks, processing
26-2?] blender animation
language models and 3d modeling
15-2?] youtube channel
manage a channel#+RESULTS: video-summary
15-2?] viudi channel
current channel
10-2?] video production
create songs with musical gears

color_cor01.png

Figure 34: media library

hardware

Sciame is a collection of projects for embedded and IoT devices

piezo_circ.png

Figure 35: management experience

sciame   dev

18-2?] coiler
coiler for pickups and sustainers
21-2?] synth
collection of synths for cheap microdevices
21-2?] dsp
dsp and effects
15-17] McAmp
mechanical amplifier
15-17] no-key-board
keyboard with no keys (touch surface
22-2?] midi-hub
midi router
97-2?] audio mixer
with op amps
19-2?] piezo buffer
for impedance match and noise cleaning

VioPreBasetta2.JPG

Figure 36: sciame library

script   dev

cd $HOME/lav/src/spiega
bash ./script/convert.sh
ls ~/lav/src/spiega/markdown/agent*

Date: 14-05-2026

Author: sabeiro

Created: 2026-06-29 Mon 13:09

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