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.ipynb_checkpoints
.ipynb_checkpoints
 
 
__pycache__
__pycache__
 
 
data
data
 
 
images
images
 
 
Classification.ipynb
Classification.ipynb
 
 
Cost Function for Linear Regression.ipynb
Cost Function for Linear Regression.ipynb
 
 
Cost functon for Logistic Regression.ipynb
Cost functon for Logistic Regression.ipynb
 
 
Decision Boundary.ipynb
Decision Boundary.ipynb
 
 
Feature Engineering and Polynomial Regression.ipynb
Feature Engineering and Polynomial Regression.ipynb
 
 
Feature Scaling and learning rate.ipynb
Feature Scaling and learning rate.ipynb
 
 
Gradient Descent for Linear Regression.ipynb
Gradient Descent for Linear Regression.ipynb
 
 
Gradient Descent for Logistic Regression.ipynb
Gradient Descent for Logistic Regression.ipynb
 
 
Linear Regression using Scikit-Learn.ipynb
Linear Regression using Scikit-Learn.ipynb
 
 
Linear Regression.ipynb
Linear Regression.ipynb
 
 
Logistic Regression Final.ipynb
Logistic Regression Final.ipynb
 
 
Logistic Regression using Scikit-Learn.ipynb
Logistic Regression using Scikit-Learn.ipynb
 
 
Logistic Regression.ipynb
Logistic Regression.ipynb
 
 
Logistic loss.ipynb
Logistic loss.ipynb
 
 
Model Function for Linear Regression.ipynb
Model Function for Linear Regression.ipynb
 
 
Multple Variable Linear Regression.ipynb
Multple Variable Linear Regression.ipynb
 
 
Overfitting.ipynb
Overfitting.ipynb
 
 
Python and Jupyter Notebooks.ipynb
Python and Jupyter Notebooks.ipynb
 
 
README.md
README.md
 
 
Regularization.ipynb
Regularization.ipynb
 
 
Vectorization.ipynb
Vectorization.ipynb
 
 
data.txt
data.txt
 
 
deeplearning.mplstyle
deeplearning.mplstyle
 
 
lab_utils_common.py
lab_utils_common.py
 
 
lab_utils_multi.py
lab_utils_multi.py
 
 
lab_utils_uni.py
lab_utils_uni.py
 
 
lab_utils_week3.py
lab_utils_week3.py
 
 
plt_logistic_loss.py
plt_logistic_loss.py
 
 
plt_one_addpt_onclick.py
plt_one_addpt_onclick.py
 
 
plt_overfit.py
plt_overfit.py
 
 
plt_quad_logistic.py
plt_quad_logistic.py
 
 
public_tests.py
public_tests.py
 
 
test_utils.py
test_utils.py
 
 
utils.py
utils.py
 
 

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Supervised-Machine-Learning

Implementation of necessary supervised machine learning algorithms for regression and classification.

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Implementation of necessary supervised machine learning algorithms for regression and classification.

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machine-learning numpy linear-regression scikit-learn classification logistic-regression matplotlib gradient-descent vectorization feature-engineering regression-models feature-scaling cost-function sigmoid-function classification-models linear-function regularization-to-avoid-overfitting logistic-loss squared-error-cost-function

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