Just a place to write
If you are reading this and you are not me, you should navigate to this link: https://ml-ops.org/ There are so many basis and nice charts that explain What is Machine Learning Operations (or ml-ops). I’m doing a summary for me 🙂 Definition of MLOps The term Machine Learning Operations is defined as “the extension of the … Read more
During Q1 one of the topics have been to learn about Artificial Intelligence, and after reading and listen several podcasts, I have decided that I would like to learn about Machine learning using Kaggle environment: python, jupyter notebooks, examples, a large community, competitions…. I have already completed the python course to refresh my knowledge and … Read more
This post is a mix review of Machine Learning type of solutions the market offers, and a quick review of some players I have in my mind. Machine Learning Wardley Map Components: After drawing this simple map, I got distracted by stocks and I put my attention on components 3 and 4: specific solutions and … Read more
This post is very boring, there are just questions and no answers. I will start with 2 questions: Which problem of my organization is the right one that investing on Machine Learning solution I will capture valuable return? What are the features of a problem that makes it the appropriate one for a ML solution? … Read more
There are multiple types of projects on machine learning, so the phases and steps are different. I will try to reduce to some basic type of projects. Basic project plans (main phases) Machine learning solution based on a Product Technology assessment = 2 – 3 days. Production trial = 8 – 12 days. Application deployment … Read more
I continue taking some basic notes of the book “Enterprise Artificial Intelligence and Machine Learning for Managers“. Tuning a machine learning model is an iterative process. Data scientists typically run numerous experiments to train and evaluate models, trying out different features, different loss functions, different AI/ML models, and adjusting model parameters and hyper-parameters. Feature engineering … Read more
I decided to read this short book published by C3.ai that is focused for managers. The book focuses on concepts and gives you the basic nomenclature to understand how these type of initiatives are implemented. Later, when you review the product list of C3 company, you realize where they are classified in terms of the … Read more
During my last learning slot I was focusing on the Wardley maps learning, the generation of content, the increase of deep knowledge and practice of mapping. This has been the second quarter I focused on it and I have the feeling I have a speed of work that can let me go to another chapter. … Read more
This guide: https://www.gartner.com/smarterwithgartner/the-cios-guide-to-artificial-intelligence , is a nice guide in case you have to have a conversation with a customer about Machine Learning or Airtificial Intelligence.
This is the second chapter of a learning process that started last September. Third Quarter The third step is defined for the next 3 months, where the main goal is to define a specific strategy of quantitative trading and work on it with real money on crypto currency market. Following the V2MOM model: Vision: Have a strategy … Read more