Do even the best DNN models understand language? New advances, new excitement Without any doubt, Deep Neural Networks (DNNs) have brought huge improvements to the NLP world recently. News like an AI model using DNN can write articles like a human or can write code to create a website like a real developer comes to …
Do even the best DNN models understand language? Read More »
Introduction In a modeling process, there are 3 core concepts that will always exist: Data. Features. Type of model and its corresponding parameters. From data to the model, features are a measurable representation of the data, which would be the format for the data to be processed by the model thus method to create features …
In a typical Machine Learning project, one would need to find out how good or bad their models are by measuring the models’ performance on a test dataset, using some statistical metrics. Various performance metrics are used for different problems, depending on what needs to be optimized by the models. For this blog, we will …
Performance Metrics for Weather Images Forecasting Read More »
[Hiring] Technical Architect at AI Lab Job Title Technical Architect Location Ho Chi Minh Contact below Type of Employment Fulltime Level Middle/Senior Report to Line Manager/Officer/Director /Project Leader If you want to join in exciting and challenging projects, MTI TECHNOLOGY could be the next destination for your career. MTI Technology AI Lab is specializes …
[Hiring]Data Scientist / Engineer Internship Job Title Data Scientist Internship Engineer internship Location Ho Chi Minh Contact recruitment@mti-tech.vn Employment Fulltime Level Internship (full-time) Report to Team Leader If you want to join in exciting and challenging projects, MTI Tech could be the next destination to your career path. MTI Technology – AI Lab specializes …
[Hiring] Data Scientist / Engineering Internship Read More »
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[Tuyển dụng] Tiến Sĩ Khoa Học Dữ Liệu tại Việt Nam – Data Scientist Read More »
Handling Missing Data – Abstract The article discusses various types of missing data and how to handle them. We demonstrate how the prediction results are affected by the quality of missing data as well as the method of handle missing data through some experiments. Introduction – Handling Missing Data For any real data set, missing data …
In this blog, we would like to introduce basic concepts in causal inference and the potential outcome framework. 1.Causality terminology Unit: The fundamental notion is that causality is tied to action (or manipulation, treatment, or intervention), applied to a unit. A unit here can be a physical object, a firm, a person, at a particular …
Causal inference and potential outcome framework Read More »
As word embeddings become more and more ubiquitous in language applications, a key issue has likewise emerged. The ability of embeddings to learn complex, underlying relationships between words is also their greatest caveat: How do we know when we have trained a good embedding? It’s important to differentiate between a good embedding in a more general sense and …
Word Embeddings – blessing or curse in disguise? Read More »
In Data Science, before building a predictive model from a particular data set, it is important to explore and perform pre-processing data. In this blog, we will illustrate some typical steps in data pre-processing. In this particular exercise, we will build a simple Decision Tree model to classify the food cuisine from the list of …
