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What is this blog about?

This blog is a collection of studies, projects and resources about some relevant topics in machine learning that I have developed during my learning path through this matter. Initially the main focus is Natural Language Processing topics, trying to describe in an easy to understand waym some of its common tasks and problems and how to face them.

I am not an advanced practicioner or expert in machine learning, so I will do my best to make you understand the concepts but for a better intuition I will provide some other links to the topics in discussion. I hope you find this blog an interesting stop on your own journey to machine learning.

Posts

• Steps to start training your custom Tensorflow model in AWS SageMaker

  Describe the most relevant steps to start training a custom algorithm in AWS SageMaker, showing how to deal with experiments and solving some of the problems when facing with custom models and SageMaker script mode on

  Nov 15, 2020

• Attention is all you need: Discovering the Transformer model

  Demystify the relevant artifacts in the paper Attention is all you need (Vaswani, Ashish & Shazeer, Noam & Parmar, Niki & Uszkoreit, Jakob & Jones, Llion & Gomez, Aidan & Kaiser, Lukasz & Polosukhin, Illia. (2017)) and build a Transformer that we will apply to a small-scale NMT problem (Neural Machine Translation)

  Oct 29, 2020

• Intro to the Encoder-Decoder model and the Attention mechanism

  Implementing an encoder-decoder model using RNNs model with Tensorflow 2, then describe the Attention mechanism and finally build an decoder with the Luong's attention. we will apply this encoder-decoder with attention to a neural machine translation problem, translating texts from English to Spanish

  Oct 7, 2020

• Character-level Text Generator using Pytorch and Amazon SageMaker

  Implementing a simple LSTM encoder-decoder model with PyTorch to familiarize ourselves with the PyTorch library and Amazon SageMaker framework. We will cover how to use Amazon Sagemaker to train a model, deploy as an endpoint service and invoke it to get some predictions

  Sep 6, 2020

• A guide on Recurrent Neural Networks: Character-level Text Generator

  A simple RNN model with PyTorch to familiarize ourselves with the PyTorch library and get started with RNNs. The goal is to build a model that can complete your sentence based on a few characters or a word used as input. In the second part, next post, we will train this model in Amazon SageMaker

  Sep 3, 2020

• Getting started with NLP: Word Embeddings, GloVe and Text classification

  We are going to explain the concepts and use of word embeddings in NLP, using Glove as an example. Then we will try to apply the pre-trained Glove word embeddings to solve a text classification problem using this technique

  Aug 15, 2020

• Getting started with NLP: Tokenization, Term-Document Matrix, TF-IDF and Text classification

  A guide on how to build a Term-Document Matrix using TF-IDF or CountVectorizer and using it to tokenize or numericalize texts for a text classification problem

  Jul 31, 2020

• A guided introduction to building a Deep Recurrent Neural Network (DRNN) from scratch

  This notebook explain and describe how to desing a deep RNN and then introduce us to the LSTM and GRU cells, a more advanced RNN designed to solve some well-known limitations of the deep, large, RNN. As the previous notebook, the texts and code section are extracted from the great book Hands-on Machine Learning with Scikit Learn ad Tensorflow First Edition

  Jul 23, 2020

• A guided introduction to building a simple Recurrent Neural Network from scratch

  A guide on building an initial and very simple recurrent neural network from scratch with Tensorflow 1, we show the math behind it in an easy to follow way. A brief summary, collection of text and code, of an excellent machine learning book Hands-on Machine Learning with Scikit Learn ad Tensorflow First Edition by Aurelien Geron

  Jul 20, 2020

• An Example Markdown Post

  A minimal example of using markdown with fastpages.

  Jan 14, 2020