RaspberryPi guys
Good source of different useful information in RaspberryPi kingdom.
Posts
Optuna good tool for hyperparameter optimization
Few weeks ago found in the Internet presentation of Optuna hyperparameter optimization framework. Optuna offers a row of cool features and I think, it could be in the toolkit of every data practitioner. This framework has ability ea eagerly search, crafted search algorithms and, of course, parallelization. Good article . Optuna's competitor is Orion project, created for black box testing of models.
FHIR
I 've been learning FHIR standard, because we gonna to build patient facing application. For a person not from US it looks like quite a hard task from the very beginning. Fortunately I have managed to find good resources. One of them was site patient.dev . This site is created by medical doctor who has also good knowledge in programming. He has illustrated practically process of building small front-end applications which communicate with different FHIR vendors (Epic, Cerner,...).
Kafka cluster locally - no pain
Recently developed distributed data science platform using service choreography architectural pattern. Solution assumed Kafka cluster as a message (event) stream provider. I tried different solutions for local Kafka cluster build for docker-compose, but the best one is from Vinsguru
In search for good ASR model
Recently I was researching models for automatic speech recognition (ASR). It seams that recently this area strives and provides us already with very interesting results. On the current moment the most popular trends are: 1. Acoustic model + language model 2. Transformers There is also trend to use CNN as more precise models, but I wonk touch it here. I think one of the important parts which is often missed is speech cancelation model - I won't concentrate on it too. Metrics The main metric used to measure ARS model efficiency is WER (word error rate). It is relation between a sum of word insertions (I), deletions (D) and substitutions (S) divided by number of words in the ground true text (N). WER = (I + D + S) / N Basically all model creators declare WER's of their models. Acoustic models I think the most common example of such a models is DeepSpeech . This framework is maintained under Mozilla foundation "wing". It provides one acoustic model and one language model...