[GigaCourse.com] Udemy - Deep Learning Prerequisites Logistic Regression in Python

1. Start Here/1. Introduction and Outline.mp4

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1. Start Here/1. Introduction and Outline.srt

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1. Start Here/2. How to Succeed in this Course.mp4

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1. Start Here/2. How to Succeed in this Course.srt

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1. Start Here/3. Review of the classification problem.mp4

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1. Start Here/3. Review of the classification problem.srt

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1. Start Here/4. Introduction to the E-Commerce Course Project.mp4

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1. Start Here/4. Introduction to the E-Commerce Course Project.srt

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1. Start Here/5. Easy first quiz.html

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2. Basics What is linear classification What's the relation to neural networks/1. Linear Classification.mp4

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2. Basics What is linear classification What's the relation to neural networks/1. Linear Classification.srt

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2. Basics What is linear classification What's the relation to neural networks/2. Biological inspiration - the neuron.mp4

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2. Basics What is linear classification What's the relation to neural networks/2. Biological inspiration - the neuron.srt

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2. Basics What is linear classification What's the relation to neural networks/3. How do we calculate the output of a neuron logistic classifier - Theory.mp4

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2. Basics What is linear classification What's the relation to neural networks/3. How do we calculate the output of a neuron logistic classifier - Theory.srt

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2. Basics What is linear classification What's the relation to neural networks/4. How do we calculate the output of a neuron logistic classifier - Code.mp4

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2. Basics What is linear classification What's the relation to neural networks/4. How do we calculate the output of a neuron logistic classifier - Code.srt

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2. Basics What is linear classification What's the relation to neural networks/5. Interpretation of Logistic Regression Output.mp4

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2. Basics What is linear classification What's the relation to neural networks/5. Interpretation of Logistic Regression Output.srt

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2. Basics What is linear classification What's the relation to neural networks/6. E-Commerce Course Project Pre-Processing the Data.mp4

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2. Basics What is linear classification What's the relation to neural networks/6. E-Commerce Course Project Pre-Processing the Data.srt

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2. Basics What is linear classification What's the relation to neural networks/7. E-Commerce Course Project Making Predictions.mp4

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2. Basics What is linear classification What's the relation to neural networks/7. E-Commerce Course Project Making Predictions.srt

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2. Basics What is linear classification What's the relation to neural networks/8. Feedforward Quiz.mp4

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2. Basics What is linear classification What's the relation to neural networks/8. Feedforward Quiz.srt

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2. Basics What is linear classification What's the relation to neural networks/9. Prediction Section Summary.mp4

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2. Basics What is linear classification What's the relation to neural networks/9. Prediction Section Summary.srt

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3. Solving for the optimal weights/1. Training Section Introduction.mp4

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3. Solving for the optimal weights/1. Training Section Introduction.srt

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3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.mp4

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3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.srt

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3. Solving for the optimal weights/11. Training Section Summary.mp4

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3. Solving for the optimal weights/11. Training Section Summary.srt

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3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.mp4

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3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.srt

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3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4

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3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt

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3. Solving for the optimal weights/4. The cross-entropy error function - Theory.mp4

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3. Solving for the optimal weights/4. The cross-entropy error function - Theory.srt

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3. Solving for the optimal weights/5. The cross-entropy error function - Code.mp4

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3. Solving for the optimal weights/5. The cross-entropy error function - Code.srt

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3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4

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3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt

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3. Solving for the optimal weights/7. Maximizing the likelihood.mp4

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3. Solving for the optimal weights/7. Maximizing the likelihood.srt

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3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.mp4

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3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.srt

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3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.mp4

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3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.srt

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4. Practical concerns/1. Practical Section Introduction.mp4

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4. Practical concerns/1. Practical Section Introduction.srt

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4. Practical concerns/10. Why Divide by Square Root of D.mp4

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4. Practical concerns/10. Why Divide by Square Root of D.srt

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4. Practical concerns/11. Practical Section Summary.mp4

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4. Practical concerns/11. Practical Section Summary.srt

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4. Practical concerns/2. Interpreting the Weights.mp4

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4. Practical concerns/2. Interpreting the Weights.srt

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4. Practical concerns/3. L2 Regularization - Theory.mp4

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4. Practical concerns/3. L2 Regularization - Theory.srt

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4. Practical concerns/4. L2 Regularization - Code.mp4

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4. Practical concerns/4. L2 Regularization - Code.srt

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4. Practical concerns/5. L1 Regularization - Theory.mp4

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4. Practical concerns/5. L1 Regularization - Theory.srt

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4. Practical concerns/6. L1 Regularization - Code.mp4

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4. Practical concerns/6. L1 Regularization - Code.srt

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4. Practical concerns/7. L1 vs L2 Regularization.mp4

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4. Practical concerns/7. L1 vs L2 Regularization.srt

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4. Practical concerns/8. The donut problem.mp4

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4. Practical concerns/8. The donut problem.srt

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4. Practical concerns/9. The XOR problem.mp4

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4. Practical concerns/9. The XOR problem.srt

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5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4

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5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt

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5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4

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5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Where to get Udemy coupons and FREE deep learning material.srt

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5. Checkpoint and applications How to make sure you know your stuff/3. BONUS Exercises + how to get good at this.mp4

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5. Checkpoint and applications How to make sure you know your stuff/3. BONUS Exercises + how to get good at this.srt

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6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4

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6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt

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6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4

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6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt

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6. Project Facial Expression Recognition/3. The class imbalance problem.mp4

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6. Project Facial Expression Recognition/3. The class imbalance problem.srt

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6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4

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6. Project Facial Expression Recognition/4. Utilities walkthrough.srt

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6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4

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6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt

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6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4

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6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt

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7. Appendix FAQ/1. What is the Appendix.mp4

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7. Appendix FAQ/1. What is the Appendix.srt

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7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4

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7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt

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7. Appendix FAQ/11. Python 2 vs Python 3.mp4

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7. Appendix FAQ/11. Python 2 vs Python 3.srt

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7. Appendix FAQ/12. What order should I take your courses in (part 1).mp4

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7. Appendix FAQ/12. What order should I take your courses in (part 1).srt

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7. Appendix FAQ/13. What order should I take your courses in (part 2).mp4

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7. Appendix FAQ/13. What order should I take your courses in (part 2).srt

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7. Appendix FAQ/14. BONUS Where to get discount coupons and FREE deep learning material.mp4

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7. Appendix FAQ/14. BONUS Where to get discount coupons and FREE deep learning material.srt

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7. Appendix FAQ/2. Gradient Descent Tutorial.mp4

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7. Appendix FAQ/2. Gradient Descent Tutorial.srt

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7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4

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7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt

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7. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4

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7. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt

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7. Appendix FAQ/5. How to Code by Yourself (part 1).mp4

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7. Appendix FAQ/5. How to Code by Yourself (part 1).srt

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7. Appendix FAQ/6. How to Code by Yourself (part 2).mp4

14.8 MB

7. Appendix FAQ/6. How to Code by Yourself (part 2).srt

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7. Appendix FAQ/7. How to Uncompress a .tar.gz file.mp4

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7. Appendix FAQ/7. How to Uncompress a .tar.gz file.srt

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7. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4

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7. Appendix FAQ/8. How to Succeed in this Course (Long Version).srt

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7. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4

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7. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt

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Readme.txt

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[GigaCourse.com].url

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