This is a collection of machine learning topics. We have to learn more in order to let machines learn from us.
We have been learning programming and AI since the beginning of this website. Now, we are excited to explore the world of generative AI art using the Stable Diffusion WebUI. This innovative web interface provides us with a simple and efficient way to generate AI art. In one of our previous posts, we experimented with […]
Easy Guide for Beginner: Learn how to use Stable Diffusion WebUI – Part 1 Read More »
We made our own Neural Machine Translator (NMT) in 2019, which helped us to translate Dutch to English. Now it is 2022, and many things have changed in the world of Data Science. The arrival of Bidirectional Encoder Representations from Transformers (BERT), a pre-trained transformer model, in 2019 brought a new page for Natural Language
The Lazy (and Easy) Pre-Trained Translator of the Year Read More »
I haven’t updated this blog for a few months. As there is something big happened in my hometown. But life must go on, so we come back here and learn a new topic — NMT (Neural Machine Translation). You may try the translate service before (if not, let’s Google Translate), it is the time we
NMT – make an easy Neural Machine Translator Read More »
In this blog, we tasted different kinds of machine learning projects so far. Our projects included prediction on stock price, image recognizer on hand writing, NLP on comment classification and others. There was one thing in common — we used long time to train a model. It is okay to use several hours for model
Save and Load your RNN model Read More »
From our Part 1 of NLP and Python topic, we talked about word pre-processing for a machine to handle words. This time, we are going to talk about building a model for a machine to classify words. We learned to use CNN to classify images in past. Then we use another neural network, Recurrent Neural
RNN (Recurrent Neural Network) in NLP and Python – Part 2 Read More »
We have handled text in machine learning using TFIDF. And we can use it to build word cloud for analytic purpose. But is it the capability of a machine can do on text? Definitely not, as we just haven’t let machine to “learn” about text yet. TFIDF is a statistics process, while we want a
Word Embedding in NLP and Python – Part 1 Read More »
Okay, I admit it, it looks like a clickbait headline :]] (yes, we did the similar thing before :]] ). But this is not a clickbait at all, as we are actually discussing this topic this time. There is a Kaggle’s challenge on predicting stock trading trend, which is a good fit for our topic.
Stock Trading with Machine Learning and Get Rich Read More »
Every business owner wants to make revenue prediction, so he or she can have better marketing decisions. On Kaggle, the data science community site, there is a challenge on making a store’s revenue prediction. And that is the topic we are looking for. The store in this challenge is none other than the Google Merchandise Store.
Revenue Prediction in Google Store Read More »
Other than our last hand writing challenge, there is another Kaggle challenge featuring image recognition — TGS Salt Identification Challenge. But this time, we are going for an “upgrade”. As we are dealing with object detection. It is all about salt. In this challenge, our mission is finding geophysical images that contain salt. Oh wait, does it sound weird? Actually
U-Net and IoU for Object Detection in Image Processing Read More »
In our past machine learning topic, “Ensemble Modeling“, we mentioned how blending helps on improving our prediction. Then in another topic, “Why are people frustrated on Kaggle’s challenge?“, we mentioned how blending ruins a data science competition. Okay, we have a question here, is blending good or bad?
Blending, the Dark Side in Data Science Competition Read More »
