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#MachineLearning – Let’s start 2020 with a free Ebook: Pattern Recognition and Machine Learning
Hi ! I’ve posted this one some time ago, however it’s still a free and VERY USEFUL one ! Christopher Bishop, Technical Fellow and Laboratory Director In Microsoft Research Cambridge, UK, gives us the chance to download for free his eBook about Pattern Recognition and Machine Learning. With more than 700 pages of a highly — read more
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#MachineLearning – Free Ebook [Pattern Recognition and Machine Learning] from Christopher Bishop
Hi ! I have already share this information on several times in face to face conversations, so I will leave a post on my blog to have the permanent reference for it. Christopher Bishop, Technical Fellow and Laboratory Director In Microsoft Research Cambridge, UK, gives us the chance to download for free his eBook about — read more
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#MachineLearning – Ebook Gratis [Pattern Recognition and Machine Learning] de Christopher Bishop
Buenas! Ya lo he comentado varias veces en persona, así que dejare un post en mi blog para tener la referencia lista. Christopher Bishop (@ChrisBishopMSFT), Technical Fellow and Laboratory Director en Microsoft Research Cambridge, UK, nos presenta la posibilidad de descarga de manera gratuita en formato PDF su libro [Pattern Recognition and Machine Learning]. Son — read more
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#MLNet – Looking at data in the Pipeline in version 0.7.0
Hi! With the new changes In Machine Learning.Net with the 0.7.0 version, the ability to peek in the data while is processed in each step of the pipeline is a little more complicated. A while ago, explain how we could do this in the post [Understanding the step bystep of Hello World]. However, ML.Net now — read more
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#MLNet – Visualizando datos del Pipeline en la versión 0.7.0
Buenas! Con los nuevos cambios en Machine Learning.Net con la versión 0.7.0, la capacidad dever paso a paso como los datos se procesan es un poco mas complicado. Hace untiempo, explique cómo podíamos hacer esto en el post [Understanding the step bystep of Hello World]. Sin embargo, ahora ML.Net utiliza Lazy objects, con lo que — read more
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#MLNET – New version 0.7 for Machine Learning.Net (the perfect excuse to update my content for next events!)
Hi! A few days ago, the Machine Learning Net. team published a new version, 0.7. I have not had time to thoroughly review the novelties of this version, however, I will update my session and demos to version 0.7 for the next session on November 22 in Mississauga Getting Started with Machine Learning.Net & Windows — read more
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#MLNET – Novedades en la version 0.7 de Machine Learning.Net (la excusa perfecta para actualizar proximos eventos!)
Buenas! Hace unos días se publico la version 0.7 de Machine Learning .Net. No he tenido tiempo de repasar a fondo las novedades de esta version, sin embargo, tendré actualizada mi sesión y demos a la version 0.7 para la próxima sesión el próximo 22 de Noviembre en Mississauga Getting Started with Machine Learning.Net & — read more
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#MLNET – Analyzing pipeline data in Machine Learning.Net using the new API 0.6.0 (thanks LINQ!)
Hi! The change in the way the pipelines work in the 0.6.0 version of Machine Learning.Net, also requires some changes in our code if we want to see how the data is processed during each of the pipeline’s steps. Using the example of my previous post, I will work with the following data structure. On — read more
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#MLNET – Analizando datos de la Pipeline con la nueva version API 0.6.0 (gracias LINQ!)
Buenas! El cambio en la forma en la que las Pipelines trabajan en la version 0.6.0 de Machine Learning.Net, también requiere que el código se modifique un poco si queremos ver como se procesan los datos durante cada uno de los pasos de la Pipeline. Retomando el ejemplo del post anterior, voy a trabajar con — read more
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#MLNET – API improvements in the new 0.6.0 version
Hi! A few days ago, the ML.Net team released the 0.6.0 version of Machine Learning.Net and one of the most important changes it’s on the way we use ML.Net API. In my MLNet sessions I usually comment on a prediction scenario based on the Label of a person to see if it is a child, — read more
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#MLNET – Cambios en la API con la nueva version 0.6.0
Buenas! Hace unos días se libero la version 0.6.0 de Machine Learning .Net y una de las novedades mas importantes de la misma fue que la API de uso de ML.Net cambio de una forma muy importante. En mis sesiones siempre suelo comentar el escenario de predicción del Label de una persona para ver si — read more
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#AutoML – Automated Machine Learning,AKA #Skynet
Hi! IMHO one of the most important announcements presented last week in Ignite was the Azure preview for AutoML: Automated Machine Learning. I’m not going to get into details about AutoML, the best option is to read the official post from the Azure Machine Learning team (see references). I’ll do my best effort to try — read more
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#AutoML – Automated Machine Learning, modelos de #MachineLearning que aprenden a optimizarse! (en las movies se llama #skynet)
Buenas! Una de las noticias mas importantes que se presentaron la semana pasada en Ignite fue la Preview de Azure AutoML: Automated Machine Learning. Lo mejor para entrar en detalles sobre AutoML es leer el post oficial del equipo de Azure Machine Learning (ver referencias). Yo lo intentare resumir en un nuevo framework que permite — read more
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#MLNET – Fix the error [System. InvalidOperationException, Entry Point ‘ Not found] when you train a pipeline
Hi! Today I’m going to leave this POST as a memory backup for me because I always forget to make this configuration in ML.Net projects and I always find the following error: System.InvalidOperationException HResult=0x80131509 Message=Entry point ‘<some external assembly> not found Source=Microsoft.ML.Data Where [External Assembly] can be For example LightGBM Message=Entry — read more
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#MLNET – Solución para el error [System.InvalidOperationException, Entry point ‘ not found] al momento de entrenar un Pipeline
Buenas! Hoy voy a dejar este post como un ayuda memoria de algo que me olvido siempre en los proyectos de ML.Net y siempre me encuentro con el siguiente error. System.InvalidOperationException HResult=0x80131509 Message=Entry point ‘<some external assembly> not found Source=Microsoft.ML.Data Donde el [External Assembly] puede ser por ejemplo LightGBM Message=Entry point — read more
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#MLNet – Adding NuGet Packages in Preview mode from MyGet, ie: Microsoft.ML-0.6.0 Version
Hi! A few days ago I wrote about the new Machine Learning.Net version 0,5. Yesterday when .NetConf started, the release was made official with the following post from Cesar de la Torre Announcing ML.NET 0.5 Now, a detail that is a little Deep in the documentation is the way to access packages in preview mode — read more
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#MLNet – Agregando paquetes en modo Preview desde MyGet, por ejemplo Microsoft.ML -Version 0.6.0
Buenas! Hace unos días hable de la nueva version 0.5 de Machine Learning.Net. Ayer cuando comenzó .NetConf, se hizo oficial el lanzamiento de esta version con el siguiente post de Cesar de la Torre Announcing ML.NET 0.5 Ahora bien, un detalle que está un poco Deep en la documentación es la forma de acceder a — read more
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#MLNET – ML.Net 0.5 initial support for #TensorFlow
Hi! New version of Machine Learning.Net and in this version, we have the ability to use TensorFlow frozen models in ML.Net. During the process of creating a pipeline, we can now use TensorFlow frozen models models and use them to train a model and make predictions. In a console application, at the time of adding — read more
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#MLNET – ML.Net 0.5 con soporte para #TensorFlow
Buenas! Nueva version de Machine Learning .Net y esta vez la novedad principal es la capacidad de utilizar modelos de TensorFlow en ML.Net. Durante el proceso de creación de una Pipeline, ahora podemos utilizar modelos frezados de TF y utilizar los mismos para entrenar un modelo y realizar predicciones. En una aplicación de Consola, al — read more
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El Bruno 