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Document : Data is stored as document that share similar traits are grouped into an index. User ↓ ⇢ search something Elasticsearch ↓ ⇢ retrieves relevant documents, then Elasticsearch presents them as search results Search Results Precision : The dots inside the white circle, the portion of the retrived data actually relevant to the search query. All the retrived results to be a perfect match to..

Customer → Server(1) ↓ ⇢ A customer serches for a product on my app ⇡ The request is sent to the server My shopping mall website(app) ↓↑ ⇢ It connected to a database which contains all my product data along with other data we're collecting from the app Database → Server(2) ↓ ⇡ looks up the product within the database ↓ ⇢ product info is sent back to the server Server(3) ↓ ⇢ product info can be r..

vi docker-compose.yml To get Elasticsearch cluster and kibana up and running in Docker, you can use Docker Compose. If you don’t want to expose port 9200 and instead use a reverse proxy, replace 9200:9200 with 127.0.0.1:9200:9200 in the docker-compose.yml file. Elasticsearch will then only be accessible from the host machine itself(www.elastic.co/guide/en/elasticsearch/reference/current/docker.h..

curl -L "https://github.com/docker/compose/releases/download/1.28.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose Install the docker-compose. # sudo curl -L "https://github.com/docker/compose/releases/download/1.28.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Tota..

Keras 1. Preprocessing from tensorflow.keras.preprocessing.text import Tokenizer t=Tokenizer() fit_text='The earth is an awesome place live' t.fit_on_texts([fit_text]) test_text='The earth is an great place live' sequences=t.texts_to_sequences([test_text])[0] sequences >>>[1, 2, 3, 4, 6, 7] t.word_index >>>{'an': 4, 'awesome': 5, 'earth': 2, 'is': 3, 'live': 7, 'place': 6, 'the': 1} Tokenizer.fi..