[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Logistic Regression in Python

Creation Time	Oct. 9, 2023, 10:02 p.m.
Last Access Time	Aug. 14, 2024, 10:12 a.m.
File Size	1.1 GB
Keywords	Tutorialsplanet Logistic Prerequisites - Deep Udemy Python Learning in NET Regression
Total Requests	13
Total Files	122
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8/1. Anaconda Environment Setup.mp4 186.3 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
1. Start Here/3. Statistics vs. Machine Learning.mp4 55.6 MB
8/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
1. Start Here/2. How to Succeed in this Course.mp4 43.8 MB
1. Start Here/1. Introduction and Outline.mp4 39.4 MB
10/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
11. Appendix FAQ Finale/2. BONUS.srt 37.8 MB
11. Appendix FAQ Finale/2. BONUS.mp4 37.8 MB
10/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.6 MB
10/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.3 MB
2/5. Interpretation of Logistic Regression Output.mp4 27.9 MB
3. Solving for the optimal weights/7. Maximizing the likelihood.mp4 25.2 MB
4. Practical concerns/8. The donut problem.mp4 24.7 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 1).mp4 24.5 MB
6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4 24.0 MB
4. Practical concerns/10. Why Divide by Square Root of D.mp4 23.5 MB
7. Background Review/1. Gradient Descent Tutorial.mp4 22.8 MB
6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21.4 MB
3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.mp4 17.1 MB
2/10. Suggestion Box.mp4 16.1 MB
2/3. How do we calculate the output of a neuron logistic classifier - Theory.mp4 15.2 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. How to Code by Yourself (part 2).mp4 14.8 MB
1. Start Here/5. Introduction to the E-Commerce Course Project.mp4 14.8 MB
4. Practical concerns/3. L2 Regularization - Theory.mp4 14.7 MB
4. Practical concerns/9. The XOR problem.mp4 14.2 MB
6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13.5 MB
10/1. How to Succeed in this Course (Long Version).mp4 13.0 MB
4. Practical concerns/6. L1 Regularization - Code.mp4 12.0 MB
5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4 11.4 MB
2/6. E-Commerce Course Project Pre-Processing the Data.mp4 11.2 MB
6. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.1 MB
6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 9.8 MB
2/2. Biological inspiration - the neuron.mp4 9.4 MB
3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.mp4 9.3 MB
3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.mp4 9.1 MB
3. Solving for the optimal weights/5. The cross-entropy error function - Code.mp4 9.1 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. Python 2 vs Python 3.mp4 7.8 MB
2/1. Linear Classification.mp4 7.5 MB
3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.mp4 7.2 MB
3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4 6.4 MB
4. Practical concerns/2. Interpreting the Weights.mp4 6.3 MB
2/4. How do we calculate the output of a neuron logistic classifier - Code.mp4 5.8 MB
2/7. E-Commerce Course Project Making Predictions.mp4 5.7 MB
11. Appendix FAQ Finale/1. What is the Appendix.mp4 5.5 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Uncompress a .tar.gz file.mp4 5.4 MB
3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5.3 MB
5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.mp4 5.3 MB
4. Practical concerns/7. L1 vs L2 Regularization.mp4 4.8 MB
4. Practical concerns/1. Practical Section Introduction.mp4 4.7 MB
3. Solving for the optimal weights/4. The cross-entropy error function - Theory.mp4 4.5 MB
4. Practical concerns/4. L2 Regularization - Code.mp4 4.5 MB
4. Practical concerns/5. L1 Regularization - Theory.mp4 4.4 MB
4. Practical concerns/11. Practical Section Summary.mp4 3.4 MB
3. Solving for the optimal weights/11. Training Section Summary.mp4 3.4 MB
1. Start Here/4. Review of the classification problem.mp4 3.0 MB
6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4 2.9 MB
3. Solving for the optimal weights/1. Training Section Introduction.mp4 2.8 MB
2/8. Feedforward Quiz.mp4 2.3 MB
2/9. Prediction Section Summary.mp4 2.2 MB
10/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.8 KB
10/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.0 KB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 1).srt 22.8 KB
8/1. Anaconda Environment Setup.srt 20.1 KB
10/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.0 KB
6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt 16.0 KB
1. Start Here/3. Statistics vs. Machine Learning.srt 14.7 KB
10/1. How to Succeed in this Course (Long Version).srt 14.7 KB
8/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.5 KB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.srt 14.1 KB
1. Start Here/5. Introduction to the E-Commerce Course Project.srt 14.0 KB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. How to Code by Yourself (part 2).srt 13.3 KB
4. Practical concerns/3. L2 Regularization - Theory.srt 11.5 KB
1. Start Here/1. Introduction and Outline.srt 10.6 KB
4. Practical concerns/10. Why Divide by Square Root of D.srt 8.7 KB
1. Start Here/2. How to Succeed in this Course.srt 8.3 KB
3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.srt 8.1 KB
6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt 8.1 KB
6. Project Facial Expression Recognition/3. The class imbalance problem.srt 8.0 KB
4. Practical concerns/8. The donut problem.srt 7.4 KB
3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.srt 7.3 KB
6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt 6.5 KB
5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt 6.4 KB
2/5. Interpretation of Logistic Regression Output.srt 6.4 KB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. Python 2 vs Python 3.srt 6.1 KB
4. Practical concerns/9. The XOR problem.srt 6.1 KB
6. Project Facial Expression Recognition/4. Utilities walkthrough.srt 5.8 KB
7. Background Review/1. Gradient Descent Tutorial.srt 5.5 KB
3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.srt 5.3 KB
3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt 5.2 KB
2/1. Linear Classification.srt 5.2 KB
2/6. E-Commerce Course Project Pre-Processing the Data.srt 5.1 KB
4. Practical concerns/2. Interpreting the Weights.srt 4.7 KB
2/10. Suggestion Box.srt 4.7 KB
4. Practical concerns/6. L1 Regularization - Code.srt 4.6 KB
2/4. How do we calculate the output of a neuron logistic classifier - Code.srt 4.5 KB
3. Solving for the optimal weights/4. The cross-entropy error function - Theory.srt 4.4 KB
2/2. Biological inspiration - the neuron.srt 4.4 KB
4. Practical concerns/7. L1 vs L2 Regularization.srt 4.3 KB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Uncompress a .tar.gz file.srt 4.2 KB
3. Solving for the optimal weights/7. Maximizing the likelihood.srt 4.0 KB
3. Solving for the optimal weights/5. The cross-entropy error function - Code.srt 3.9 KB
2/3. How do we calculate the output of a neuron logistic classifier - Theory.srt 3.9 KB
5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.srt 3.8 KB
4. Practical concerns/5. L1 Regularization - Theory.srt 3.7 KB
11. Appendix FAQ Finale/1. What is the Appendix.srt 3.7 KB
4. Practical concerns/1. Practical Section Introduction.srt 3.5 KB
2/7. E-Commerce Course Project Making Predictions.srt 3.0 KB
4. Practical concerns/11. Practical Section Summary.srt 2.6 KB
3. Solving for the optimal weights/11. Training Section Summary.srt 2.6 KB
3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.srt 2.5 KB
3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt 2.3 KB
1. Start Here/4. Review of the classification problem.srt 2.2 KB
3. Solving for the optimal weights/1. Training Section Introduction.srt 2.0 KB
2/8. Feedforward Quiz.srt 1.7 KB
4. Practical concerns/4. L2 Regularization - Code.srt 1.6 KB
6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt 1.6 KB
2/9. Prediction Section Summary.srt 1.5 KB
1. Start Here/6. Easy first quiz.html 152 bytes
1. Start Here/[Tutorialsplanet.NET].url 128 bytes
7. Background Review/[Tutorialsplanet.NET].url 128 bytes
[Tutorialsplanet.NET].url 128 bytes

[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Logistic Regression in Python

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