diff --git a/longinus/longinus/coeff_encoders/encoder.py b/longinus/longinus/coeff_encoders/encoder.py
deleted file mode 100644
index fd54ccb..0000000
--- a/longinus/longinus/coeff_encoders/encoder.py
+++ /dev/null
@@ -1,7 +0,0 @@
-class Encoder:
-    def __init__(self, encoder):
-        self.encoder = encoder
-    
-    def train_model(self, dataset):
-
-        pass
diff --git a/longinus/longinus/coeff_encoders/knn.py b/longinus/longinus/coeff_encoders/knn.py
deleted file mode 100644
index e69de29..0000000
diff --git a/longinus/longinus/coeff_encoders/neural_network.py b/longinus/longinus/coeff_encoders/neural_network.py
index 44fd5c7..1722e10 100644
--- a/longinus/longinus/coeff_encoders/neural_network.py
+++ b/longinus/longinus/coeff_encoders/neural_network.py
@@ -1,3 +1,32 @@
+from keras.models import Sequential, load_model
+from keras.layers import Conv2D, MaxPooling2D, Flatten, Dense
+import pandas as pd
+
+
 class NeuralNetworkEncoder:
-    def __init__(self):
-        pass
+    def __init__(self, internal_activation_function: str, external_activation_function: str, optimizer: str, loss_function: str, image_dimension_x: int, image_dimension_y: int):
+        self.model = Sequential()
+        self.model.add(Conv2D(32, (3, 3), activation=internal_activation_function, input_shape=(image_dimension_x, image_dimension_y, 1)))
+        self.model.add(MaxPooling2D((2, 2)))
+        self.model.add(Conv2D(64, (3, 3), activation=internal_activation_function))
+        self.model.add(MaxPooling2D((2, 2)))
+        self.model.add(Flatten())
+        self.model.add(Dense(64, activation=internal_activation_function))
+        self.model.add(Dense((8, 8), activation=external_activation_function))
+        self.model.compile(optimizer=optimizer, loss=loss_function)
+    
+    def __init__(self, pretrained_weights_path: str):
+        self.model = load_model(pretrained_weights_path)
+
+    def train(self, train_imageset: pd.DataFrame, train_quantization_dataset: pd.DataFrame, validation_dataset: pd.DataFrame, validation_quantization_dataset: pd.DataFrame, epochs: int, batch_size: int):
+        self.model.fit(train_imageset, train_quantization_dataset, validation_data=(validation_dataset, validation_quantization_dataset), epochs=epochs, batch_size=batch_size)
+
+    def export_weights(self, output_path: str):
+        self.model.save(output_path)
+
+    def evaluate(self, test_imageset: pd.DataFrame, test_quantization_dataset: pd.DataFrame):
+        return self.model.evaluate(test_imageset, test_quantization_dataset)
+
+    def predict_quantization_table(self, imageset: pd.DataFrame):
+        return self.model.predict(imageset)
+    
diff --git a/longinus/longinus/coeff_encoders/random_forest.py b/longinus/longinus/coeff_encoders/random_forest.py
deleted file mode 100644
index e19bc6c..0000000
--- a/longinus/longinus/coeff_encoders/random_forest.py
+++ /dev/null
@@ -1,19 +0,0 @@
-import numpy as np
-from sklearn.ensemble import RandomForestRegressor
-from sklearn.model_selection import cross_val_score
-from sklearn.model_selection import train_test_split
-
-class RandomForestEncoder:
-    def __init__(self):
-        self.engine = RandomForestRegressor(n_estimators=100, max_depth=10)
-        self.dataset_training_X = None
-        self.dataset_training_y = None
-        self.dataset_testing_X = None
-        self.dataset_testing_y = None
-
-    def train_model(self, dataset):
-        self.dataset_training_X, self.dataset_training_y, self.dataset_testing_X, self.dataset_testing_y = train_test_split(dataset, test_size=0.2)
-        self.engine.fit(self.dataset_training_X, self.dataset_training_y)
-    
-    def evaluate_model(self):
-        return cross_val_score(self.engine, self.dataset_testing_X, self.dataset_testing_y)
diff --git a/longinus/longinus/coeff_encoders/svm.py b/longinus/longinus/coeff_encoders/svm.py
deleted file mode 100644
index e69de29..0000000
diff --git a/longinus/longinus/utils/dataset.py b/longinus/longinus/utils/dataset.py
index b8f4627..91ac3db 100644
--- a/longinus/longinus/utils/dataset.py
+++ b/longinus/longinus/utils/dataset.py
@@ -32,6 +32,16 @@ class Dataset():
                 self.dataset_filenames.append(new_filename)
         self.dataset_size = counter
     
+    def load_prepared_dataset(self):
+        for filename in os.listdir(self.dataset_path):
+            if os.path.isfile(file):
+                counter += 1
+            else:
+                continue
+            file = os.path.join(self.dataset_path, filename)
+            self.dataset_filenames.append(file)
+            
+
     def __len__(self):
         return self.dataset_size
     
diff --git a/longinus/poetry.lock b/longinus/poetry.lock
index dfb4c6e..1fe3233 100644
--- a/longinus/poetry.lock
+++ b/longinus/poetry.lock
@@ -1,5 +1,194 @@
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+]
+
+[[package]]
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+optional = false
+python-versions = ">=3.8"
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+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
+]
+
+[[package]]
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+]
+
 [[package]]
 name = "click"
 version = "8.1.7"
@@ -14,6 +203,23 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "cloudpathlib"
+version = "0.16.0"
+description = "pathlib-style classes for cloud storage services."
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.extras]
+all = ["cloudpathlib[azure]", "cloudpathlib[gs]", "cloudpathlib[s3]"]
+azure = ["azure-storage-blob (>=12)"]
+gs = ["google-cloud-storage"]
+s3 = ["boto3"]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -25,6 +231,21 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "confection"
+version = "0.1.4"
+description = "The sweetest config system for Python"
+optional = false
+python-versions = ">=3.6"
+files = [
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+]
+
+[package.dependencies]
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+srsly = ">=2.4.0,<3.0.0"
+
 [[package]]
 name = "contourpy"
 version = "1.2.1"
@@ -103,6 +324,48 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
+name = "cymem"
+version = "2.0.8"
+description = "Manage calls to calloc/free through Cython"
+optional = false
+python-versions = "*"
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 version = "4.51.0"
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 unicode = ["unicodedata2 (>=15.1.0)"]
 woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
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+description = "Internationalized Domain Names in Applications (IDNA)"
+optional = false
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+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
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 name = "joblib"
 version = "1.4.0"
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+h5py = "*"
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+namex = "*"
+numpy = "*"
+optree = "*"
+rich = "*"
+
+[[package]]
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+description = "Keras Models Hub"
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+pathlib = "*"
+Pillow = "*"
+spacy = "*"
+
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 name = "kiwisolver"
 version = "1.4.5"
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+
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+test = ["pytest", "pytest-cov"]
+
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 python-dateutil = ">=2.7"
 
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 version = "1.26.4"
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 ]
 
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+test = ["pytest", "pytest-cov", "pytest-xdist"]
+torch = ["torch"]
+
 [[package]]
 name = "packaging"
 version = "24.0"
@@ -490,6 +1244,17 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.9.2)"]
 
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 version = "10.3.0"
@@ -576,6 +1341,176 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa
 typing = ["typing-extensions"]
 xmp = ["defusedxml"]
 
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+
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@@ -733,6 +1707,22 @@ dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest
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+setuptools = "*"
+srsly = ">=2.4.0,<3.0.0"
+wasabi = ">=0.8.1,<1.2.0"
+
+[package.extras]
+cuda = ["cupy (>=5.0.0b4)"]
+cuda-autodetect = ["cupy-wheel (>=11.0.0)"]
+cuda100 = ["cupy-cuda100 (>=5.0.0b4)"]
+cuda101 = ["cupy-cuda101 (>=5.0.0b4)"]
+cuda102 = ["cupy-cuda102 (>=5.0.0b4)"]
+cuda110 = ["cupy-cuda110 (>=5.0.0b4)"]
+cuda111 = ["cupy-cuda111 (>=5.0.0b4)"]
+cuda112 = ["cupy-cuda112 (>=5.0.0b4)"]
+cuda113 = ["cupy-cuda113 (>=5.0.0b4)"]
+cuda114 = ["cupy-cuda114 (>=5.0.0b4)"]
+cuda115 = ["cupy-cuda115 (>=5.0.0b4)"]
+cuda116 = ["cupy-cuda116 (>=5.0.0b4)"]
+cuda117 = ["cupy-cuda117 (>=5.0.0b4)"]
+cuda11x = ["cupy-cuda11x (>=11.0.0)"]
+cuda12x = ["cupy-cuda12x (>=11.5.0)"]
+cuda80 = ["cupy-cuda80 (>=5.0.0b4)"]
+cuda90 = ["cupy-cuda90 (>=5.0.0b4)"]
+cuda91 = ["cupy-cuda91 (>=5.0.0b4)"]
+cuda92 = ["cupy-cuda92 (>=5.0.0b4)"]
+datasets = ["ml-datasets (>=0.2.0,<0.3.0)"]
+mxnet = ["mxnet (>=1.5.1,<1.6.0)"]
+tensorflow = ["tensorflow (>=2.0.0,<2.6.0)"]
+torch = ["torch (>=1.6.0)"]
+
 [[package]]
 name = "threadpoolctl"
 version = "3.4.0"
@@ -755,6 +2004,58 @@ files = [
     {file = "threadpoolctl-3.4.0.tar.gz", hash = "sha256:f11b491a03661d6dd7ef692dd422ab34185d982466c49c8f98c8f716b5c93196"},
 ]
 
+[[package]]
+name = "tqdm"
+version = "4.66.4"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
+[[package]]
+name = "typer"
+version = "0.9.4"
+description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "typer-0.9.4-py3-none-any.whl", hash = "sha256:aa6c4a4e2329d868b80ecbaf16f807f2b54e192209d7ac9dd42691d63f7a54eb"},
+    {file = "typer-0.9.4.tar.gz", hash = "sha256:f714c2d90afae3a7929fcd72a3abb08df305e1ff61719381384211c4070af57f"},
+]
+
+[package.dependencies]
+click = ">=7.1.1,<9.0.0"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
+dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"]
+doc = ["cairosvg (>=2.5.2,<3.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pillow (>=9.3.0,<10.0.0)"]
+test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.971)", "pytest (>=4.4.0,<8.0.0)", "pytest-cov (>=2.10.0,<5.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<4.0.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
+
+[[package]]
+name = "typing-extensions"
+version = "4.11.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "typing_extensions-4.11.0-py3-none-any.whl", hash = "sha256:c1f94d72897edaf4ce775bb7558d5b79d8126906a14ea5ed1635921406c0387a"},
+    {file = "typing_extensions-4.11.0.tar.gz", hash = "sha256:83f085bd5ca59c80295fc2a82ab5dac679cbe02b9f33f7d83af68e241bea51b0"},
+]
+
 [[package]]
 name = "tzdata"
 version = "2024.1"
@@ -766,7 +2067,60 @@ files = [
     {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
 ]
 
+[[package]]
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+version = "2.2.1"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
+[[package]]
+name = "wasabi"
+version = "1.1.2"
+description = "A lightweight console printing and formatting toolkit"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "wasabi-1.1.2-py3-none-any.whl", hash = "sha256:0a3f933c4bf0ed3f93071132c1b87549733256d6c8de6473c5f7ed2e171b5cf9"},
+    {file = "wasabi-1.1.2.tar.gz", hash = "sha256:1aaef3aceaa32edb9c91330d29d3936c0c39fdb965743549c173cb54b16c30b5"},
+]
+
+[package.dependencies]
+colorama = {version = ">=0.4.6", markers = "sys_platform == \"win32\" and python_version >= \"3.7\""}
+
+[[package]]
+name = "weasel"
+version = "0.3.4"
+description = "Weasel: A small and easy workflow system"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "weasel-0.3.4-py3-none-any.whl", hash = "sha256:ee48a944f051d007201c2ea1661d0c41035028c5d5a8bcb29a0b10f1100206ae"},
+    {file = "weasel-0.3.4.tar.gz", hash = "sha256:eb16f92dc9f1a3ffa89c165e3a9acd28018ebb656e0da4da02c0d7d8ae3f6178"},
+]
+
+[package.dependencies]
+cloudpathlib = ">=0.7.0,<0.17.0"
+confection = ">=0.0.4,<0.2.0"
+packaging = ">=20.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
+requests = ">=2.13.0,<3.0.0"
+smart-open = ">=5.2.1,<7.0.0"
+srsly = ">=2.4.3,<3.0.0"
+typer = ">=0.3.0,<0.10.0"
+wasabi = ">=0.9.1,<1.2.0"
+
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "e09afe504acf99e46d7076ec1baf99babfaa73f106fbb165be626e221d4ab12e"
+content-hash = "b7429bfb6eb6d2c2e39965142c28ab322972aae37f652f5e64f023dfbc3f79b0"
diff --git a/longinus/pyproject.toml b/longinus/pyproject.toml
index f3a93e3..22d28e3 100644
--- a/longinus/pyproject.toml
+++ b/longinus/pyproject.toml
@@ -17,6 +17,8 @@ pillow = "^10.2.0"
 scipy = "^1.12.0"
 scikit-learn = "^1.4.1.post1"
 opencv-python = "^4.9.0.80"
+keras = "^3.3.3"
+keras-models = "^0.0.7"
 
 
 [build-system]