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Updated index file with insertion of step 3 for hactoberfest
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Tusharbecoding authored Oct 5, 2022
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Expand Up @@ -365,6 +365,208 @@ <h6>Practice lab: Linear regression</h6>
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<div class="step three">
<div class="circle hello3">
<i class="fas fa-graduation-cap"></i>
<h4 class="header4">WEEK 3<br />Classification</h4>
</div>
<article data-step="9" class="header3">
<header class="d-flex align-items-center header3">
<i class="fas fa-graduation-cap"></i>
<h6 class="header3">Classification with logistic regression</h6>
</header>

<div class="body ">
<a href="https://www.coursera.org/learn/machine-learning/lecture/aoMt6/motivations" target="_blank" rel="noopener noreferrer">
Motivations
</a>
<input type="checkbox" id="option44"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/0Ew8Q/optional-lab-classification" target="_blank" rel="noopener noreferrer">
Optional lab: Classification
</a>
<input type="checkbox" id="option45"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/zNxaw/logistic-regression" target="_blank" rel="noopener noreferrer">
Logistic Regression
</a>
<input type="checkbox" id="option46"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/9LMHw/optional-lab-sigmoid-function-and-logistic-regression" target="_blank" rel="noopener noreferrer">
Optional lab: Sigmoid function and logistic regression
</a>
<input type="checkbox" id="option47"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/kIf25/optional-lab-feature-scaling-and-learning-rate" target="_blank" rel="noopener noreferrer">
Optional lab: Feature scaling and learning rate
</a>
<input type="checkbox" id="option48"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/qrxwU/decision-boundary" target="_blank" rel="noopener noreferrer">
Decision Boundary
</a>
<input type="checkbox" id="option49"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/ULi82/optional-lab-decision-boundary" target="_blank" rel="noopener noreferrer">
Optional lab: Decision Boundary
</a>
<input type="checkbox" id="option50"> <br>
<a href="https://www.coursera.org/learn/machine-learning/exam/jkmDN/practice-quiz-classification-with-logistic-regression" target="_blank" rel="noopener noreferrer">
Practice Quiz: Classification with logistic regression
</a>
<div class="d-flex justify-content-between mt-3 controls">
<a class="btn btn-outline-danger" href="#">Prev</a>
<a class="btn btn-outline-danger" href="#">Next</a>
</div>
</div>
</article>
<article data-step="10" >
<header class="d-flex align-items-center header3">
<i class="fas fa-graduation-cap"></i>
<h6 class="header3">Cost function for logistic regression</h6>
</header>

<div class="body ">
<a href="https://www.coursera.org/learn/machine-learning/lecture/0hpr8/cost-function-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Cost function for logistic regression
</a>
<input type="checkbox" id="option51"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/pOtDs/optional-lab-logistic-loss" target="_blank" rel="noopener noreferrer">
Optional lab: Logistic Loss
</a>
<input type="checkbox" id="option52"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/Zjj2j/simplified-cost-function-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Simplified Cost function for logistic regression
</a>
<input type="checkbox" id="option53"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/m9laL/optional-lab-cost-function-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Optional lab: Cost function for logistic regression
</a>
<input type="checkbox" id="option54"> <br>
<a href="https://www.coursera.org/learn/machine-learning/exam/tGUIZ/practice-quiz-cost-function-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Practice Quiz: Cost function for logistic regression
</a>
<input type="checkbox" id="option55"> <br>
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<div class="d-flex justify-content-between mt-3 controls">
<a class="btn btn-outline-danger" href="#">Prev</a>
<a class="btn btn-outline-danger" href="#">Next</a>
</div>
</div>
</article>
<article data-step="11">
<header class="d-flex align-items-center header3">
<i class="fas fa-graduation-cap"></i>
<h6 class="header3">Gradient descent for logistic regression</h6>
</header>

<div class="body">
<a href="https://www.coursera.org/learn/machine-learning/lecture/Ha1RP/gradient-descent-implementation" target="_blank" rel="noopener noreferrer">
Gradient descent implementation
</a>
<input type="checkbox" id="option56"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/KtxCL/optional-lab-gradient-descent-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Optional lab: Gradient descent for logistic regression
</a>
<input type="checkbox" id="option57"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/zNxaw/logistic-regression" target="_blank" rel="noopener noreferrer">
Optional lab: Logistic Regression with scikit-learn
</a>
<input type="checkbox" id="option58"> <br>
<a href="https://www.coursera.org/learn/machine-learning/exam/XqVmD/practice-quiz-gradient-descent-for-logistic-regression" target="_blank" rel="noopener noreferrer">
Practice Quiz: Gradient descent for logistic regression
</a>
<input type="checkbox" id="option59"> <br>
<!-- <small> Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. </small> -->
<div class="d-flex justify-content-between mt-3 controls">
<a class="btn btn-outline-danger" href="#">Prev</a>
<a class="btn btn-outline-danger" href="#">Next</a>
</div>
</div>
</article>
<article data-step="12">
<header class="d-flex align-items-center header3">
<i class="fas fa-graduation-cap"></i>
<h6 class="header3">The problem of overfitting</h6>
</header>

<div class="body">
<a href="https://www.coursera.org/learn/machine-learning/lecture/erGPe/the-problem-of-overfitting" target="_blank" rel="noopener noreferrer">
The problem of overfitting
</a>
<input type="checkbox" id="option60"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/HvDkF/addressing-overfitting" target="_blank" rel="noopener noreferrer">
Addressing overfitting
</a>
<input type="checkbox" id="option61"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/3nraU/optional-lab-overfitting" target="_blank" rel="noopener noreferrer">
Optional lab: Overfitting
</a>
<input type="checkbox" id="option62"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/UZTPk/cost-function-with-regularization" target="_blank" rel="noopener noreferrer">
Cost function with regularization
</a>
<input type="checkbox" id="option63"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/WRULa/regularized-linear-regression" target="_blank" rel="noopener noreferrer">
Regularized linear regularization
</a>
<input type="checkbox" id="option64"> <br>
<a href="https://www.coursera.org/learn/machine-learning/lecture/cAxpF/regularized-logistic-regression" target="_blank" rel="noopener noreferrer">
Regularized logistic regularization
</a>
<input type="checkbox" id="option65"> <br>
<a href="https://www.coursera.org/learn/machine-learning/ungradedLab/36A9A/optional-lab-regularization" target="_blank" rel="noopener noreferrer">
Optional lab: Regularization
</a>
<input type="checkbox" id="option66"> <br>
<a href="https://www.coursera.org/learn/machine-learning/exam/8Kf7N/practice-quiz-the-problem-of-overfitting" target="_blank" rel="noopener noreferrer">
Practice quiz: The problem of overfitting
</a>
<input type="checkbox" id="option67"> <br>
<!-- <small> Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. </small> -->
<div class="d-flex justify-content-between mt-3 controls">
<a class="btn btn-outline-danger" href="#">Prev</a>
<a class="btn btn-outline-danger" href="#">Next</a>
</div>
</div>
</article>
<article data-step="15">
<header class="d-flex align-items-center header3">
<i class="fas fa-graduation-cap"></i>
<h6 class="header3">PRACTICE LAB: Logistic Regression</h6>
</header>

<div class="body">
<a href="https://www.coursera.org/learn/machine-learning/programming/vPfeK/week-3-practice-lab-logistic-regression" target="_blank" rel="noopener noreferrer">
Start
</a>
<input type="checkbox" id="option68"> <br>
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<a class="btn btn-outline-danger" href="#">Prev</a>
<a class="btn btn-outline-danger" href="#">Next</a>
</div>
</div>
</article>
<div class="spacer">
<div>

</div>
</div>
<article data-step="16">
<header class="d-flex align-items-center">
<i class="fas fa-flag-checkered" style="font-size: 4em; padding: 20px"></i>
<h6>Acknowledgments</h6>
</header>

<h6></h6>
<div class="body">
<a href="https://www.coursera.org/learn/machine-learning/supplement/ZeEqX/acknowledgments" target="_blank" rel="noopener noreferrer">
Acknowledgments
</a>
<input type="checkbox" id="option69"> <br>
</div>
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<a class="btn btn-outline-danger" href="#">Prev</a>
</div>
</div>
</article>
</div>
</div>
<!-- partial -->
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