Initial commit

.gitignore

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+advanced_sentiments_build/
+name_gender_build/

Makefile

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+build_name_gender:
+	python3 -m coffeehouse_dltc --train-model name_gender
+
+build_email_contents:
+	python3 -m coffeehouse_dltc --train-model advanced_sentiments
+
+build:
+	make build_name_gender
+	make build_email_contents
+
+test_name_gender:
+	python3 -m coffeehouse_dltc --test-model name_gender_build
+
+test_advanced_sentiments:
+	python3 -m coffeehouse_dltc --test-model advanced_sentiments_build
+
+clean:
+	@for f in $(shell ls name_gender); do \
+		echo "Processing $${f}" && sort -u "name_gender/$${f}" > "name_gender/$${f}.clean" && rm "name_gender/$${f}" && mv "name_gender/$${f}.clean" "name_gender/$${f}"; \
+	done
+	@for f in $(shell ls advanced_sentiments); do \
+		echo "Processing $${f}" && sort -u "advanced_sentiments/$${f}" > "advanced_sentiments/$${f}.clean" && rm "advanced_sentiments/$${f}" && mv "advanced_sentiments/$${f}.clean" "advanced_sentiments/$${f}"; \
+	done

README.md

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+# ProfileIO
+
+This is the source code for ProfileIO models which are intended to be used to
+identify specifhic characters about individuals.
+
+## Fetch model
+
+CoffeeHousePy comes with tools to fetch the latest models available, add the
+following code to your project to fetch the model
+
+```python
+from resource_fetch import ResourceFetch
+rf = ResourceFetch()
+
+spam_classification = rf.fetch("Intellivoid", "CoffeeHouseData-ProfileIO")
+```
+
+
+## Building The Model
+
+Builiding the model requires CoffeeHousePy to be installed on the system, 
+you can build the model in the foreground by running one of these commands
+
+```sh
+# Build the model (Full)
+make build
+
+# Build advanced_sentiments
+make build_advaned_sentiments
+
+# Build name_gender
+make build_name_gender
+```
+
+
+## Testing the model
+
+You can run an interactive Commandline Interface test to predict
+the output of the model's predictions by running the DLTC tester.
+
+```sh
+make test_advanced_sentiments
+make test_name_gender
+```
+
+
+## Cleaning the data
+
+Once the data is generated, it's reccomended to clean the and
+organize the new data that was generated.
+
+```sh
+make clean
+```

advanced_sentiments/model.json

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+{
+    "model": {
+        "name": "Advanced Sentiments",
+        "model_name": "advanced_sentiments",
+        "author": "Zi Xing",
+        "version": "1.0.0.0",
+        "description": "Model for predicting multiple sentminal emotions towards user input"
+    },
+    "training_properties":{
+        "epoch": 15,
+        "vec_dim": 100,
+        "test_ratio": 0.2,
+        "architecture": "cnn",
+        "batch_size": 64
+    },
+    "classification": [
+        {"l": "anger", "f": "anger.dat"},
+        {"l": "neutral", "f": "neutral.dat"},
+        {"l": "happiness", "f": "happiness.dat"},
+        {"l": "affection", "f": "affection.dat"},
+        {"l": "sadness", "f": "sadness.dat"}
+    ]
+}

name_gender/model.json

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+{
+    "model": {
+        "name": "Name Gender Prediction",
+        "model_name": "name_gender",
+        "author": "Zi Xing",
+        "version": "1.0.0.0",
+        "description": "Model for predicting the the gender based off a name"
+    },
+    "training_properties":{
+        "epoch": 30,
+        "vec_dim": 100,
+        "test_ratio": 0.2,
+        "architecture": "cnn",
+        "batch_size": 64
+    },
+    "classification": [
+        {"l": "male", "f": "male_names.dat"},
+        {"l": "female", "f": "female_names.dat"}
+    ]
+}