├── Books ├── DeepLearningwithPython - Jason Brownlee │ ├── Chapter 10. Project_Multiclass Classification Of Flower Species.ipynb │ ├── Chapter 11.Project_Binary Classification Of Sonar Returns.ipynb │ ├── Chapter 5. Project_Develop Large Models on GPUs Cheaply In the Cloud(AWS).ipynb │ ├── Chapter 8. Evaluate The Performance of Deep Learning Models.ipynb │ ├── Chapter 9. Use Keras Models With Scikit-Learn For General Machine Learning.ipynb │ ├── Chapter12_Regression_of_Boston_House_Prices.ipynb │ ├── Chapter2.IntroductionToTheano.ipynb │ ├── Chapter3.IntroductiontoTensorFlow.ipynb │ ├── Chapter4.IntroductiontoKeras.ipynb │ ├── Chapter6.CrashCourseInMulti-LayerPerceptrons.ipynb │ ├── Chapter7. Develop Your First Neural Network With keras.ipynb │ ├── housing.csv │ ├── ionosphere.csv │ ├── iris.csv │ ├── pima-indians-diabetes.csv │ └── sonar.csv └── Machine Learning Mastery With Python - Jason Brownlee │ ├── Chapter10.MachineLearning AlgorithmPerformanceMetrics.ipynb │ ├── Chapter11.SpotCheckClassificationAlgorithms.ipynb │ ├── Chapter12.Spot-CheckRegresssionAlgorithms Do.ipynb │ ├── Chapter13.CompareMachineLearningAlgorithms.ipynb │ ├── Chapter14.AutomateMachineLearningWorkflowsWithPipelines.ipynb │ ├── Chapter15.ImprovePerformancewithEnsembles.ipynb │ ├── Chapter16.ImprovePerformancewithAlgorithmTuning.ipynb │ ├── Chapter17.SaveandLoadMachineLearningModels.ipynb │ ├── Chapter18.PredictiveModelingProjectTemplate.ipynb │ ├── Chapter19.YourFirstMachineLearningProjectinPythonStepByStep.ipynb │ ├── Chapter21.BinaryClassificationMachineLearningCaseStudyProject.ipynb │ ├── Chapter5.UnderstandYourDataWithDescriptiveStatistics.ipynb │ ├── Chapter6.UnderstandYourDataWithVisualization.ipynb │ ├── Chapter7.PrepareYourDataForMachineLearning.ipynb │ ├── Chapter8. Feature Selection For Machine Learning.ipynb │ └── Chapter9.EvaluatePerformanceMachineLEarningAlgorithmsResamling.ipynb ├── Course └── Deep Learning Specialization │ ├── Improveing Deep Neural Networks │ ├── Assignments │ │ ├── GradientChecking.ipynb │ │ ├── Initialization.ipynb │ │ └── Regularization.ipynb │ ├── Optimization algorithms.ipynb │ ├── Week1. Practical aspects of Deep Learning.ipynb │ └── img │ │ ├── Screen Shot 2019-01-20 at 11.31.33.png │ │ ├── Screen Shot 2019-01-20 at 11.38.51.png │ │ ├── Screen Shot 2019-01-20 at 12.10.35.png │ │ ├── Screen Shot 2019-01-20 at 12.17.39.png │ │ ├── Screen Shot 2019-01-20 at 18.31.16.png │ │ ├── Screen Shot 2019-01-20 at 23.10.38.png │ │ ├── Screen Shot 2019-01-20 at 23.58.04.png │ │ ├── Screen Shot 2019-01-21 at 0.50.40.png │ │ ├── Screen Shot 2019-01-21 at 0.56.43.png │ │ ├── Screen Shot 2019-01-21 at 1.24.29.png │ │ ├── Screen Shot 2019-01-21 at 1.48.17 (2).png │ │ ├── Screen Shot 2019-01-21 at 2.00.31.png │ │ ├── Screen Shot 2019-01-21 at 2.02.21.png │ │ ├── Screen Shot 2019-01-22 at 0.10.35.png │ │ ├── Screen Shot 2019-01-22 at 7.21.05.png │ │ ├── Screen Shot 2019-01-22 at 7.23.37.png │ │ ├── Screen Shot 2019-01-22 at 7.41.06.png │ │ └── Screen Shot 2019-02-01 at 22.33.14.png │ └── Neural Networks and Deep Learning- Coursera │ ├── Assignments │ ├── .ipynb_checkpoints │ │ └── Planar+data+classification+with+one+hidden+layer+v5 (1)-checkpoint.ipynb │ ├── Building+your+Deep+Neural+Network+-+Step+by+Step+v8.ipynb │ ├── Deep+Neural+Network+-+Application+v8.ipynb │ ├── Logistic+Regression+with+a+Neural+Network+mindset+v5.ipynb │ ├── Planar+data+classification+with+one+hidden+layer+v5.ipynb │ └── Python+Basics+With+Numpy+v3.ipynb │ ├── Week1. Introduction Deep Learning.ipynb │ ├── Week2. Neutral Networks Basics.ipynb │ ├── Week3. Shallow Neural Network.ipynb │ ├── Week4. Deep Neural Network.ipynb │ └── img │ ├── Screen Shot 2019-01-13 at 16.11.52.png │ ├── Screen Shot 2019-01-13 at 16.17.59.png │ ├── Screen Shot 2019-01-13 at 16.23.50.png │ ├── Screen Shot 2019-01-13 at 16.40.34.png │ ├── Screen Shot 2019-01-13 at 17.10.42.png │ ├── Screen Shot 2019-01-13 at 22.26.10.png │ ├── Screen Shot 2019-01-13 at 22.39.24.png │ ├── Screen Shot 2019-01-13 at 22.43.22.png │ ├── Screen Shot 2019-01-13 at 23.04.01.png │ ├── Screen Shot 2019-01-13 at 23.25.05.png │ ├── Screen Shot 2019-01-13 at 23.28.06.png │ ├── Screen Shot 2019-01-14 at 0.20.04.png │ ├── Screen Shot 2019-01-14 at 1.02.58.png │ ├── Screen Shot 2019-01-14 at 1.09.34.png │ ├── Screen Shot 2019-01-14 at 1.41.38.png │ ├── Screen Shot 2019-01-14 at 13.39.46.png │ ├── Screen Shot 2019-01-14 at 13.49.19.png │ ├── Screen Shot 2019-01-14 at 13.54.30.png │ ├── Screen Shot 2019-01-14 at 14.44.55.png │ ├── Screen Shot 2019-01-14 at 14.46.02.png │ ├── Screen Shot 2019-01-14 at 14.58.28.png │ ├── Screen Shot 2019-01-14 at 17.35.10.png │ ├── Screen Shot 2019-01-14 at 17.39.55.png │ ├── Screen Shot 2019-01-14 at 17.40.35.png │ ├── Screen Shot 2019-01-14 at 18.20.09.png │ ├── Screen Shot 2019-01-14 at 20.35.03.png │ ├── Screen Shot 2019-01-14 at 21.25.36.png │ ├── Screen Shot 2019-01-14 at 21.31.47.png │ ├── Screen Shot 2019-01-14 at 21.37.10.png │ ├── Screen Shot 2019-01-16 at 1.03.00.png │ ├── Screen Shot 2019-01-16 at 1.32.49.png │ ├── Screen Shot 2019-01-16 at 1.41.13.png │ ├── Screen Shot 2019-01-16 at 23.25.08.png │ ├── Screen Shot 2019-01-17 at 22.08.52.png │ ├── Screen Shot 2019-01-17 at 22.30.12.png │ ├── Screen Shot 2019-01-17 at 23.02.08.png │ ├── Screen Shot 2019-01-18 at 0.42.33.png │ ├── Screen Shot 2019-01-18 at 1.07.31.png │ ├── Screen Shot 2019-01-18 at 1.08.10.png │ ├── Screen Shot 2019-01-18 at 1.09.37.png │ ├── Screen Shot 2019-01-18 at 1.10.07.png │ ├── Screen Shot 2019-01-18 at 1.30.21.png │ ├── Screen Shot 2019-01-19 at 17.46.30.png │ ├── Screen Shot 2019-01-19 at 23.13.23.png │ └── Screen Shot 2019-01-19 at 23.40.20.png ├── Deep Learning Specialization.png ├── End-to-End Machine Learning with TensorFlow on GCP.png ├── House_Price_Advanced_Regression_Techniques.ipynb ├── Lesson1_Introduction_to_our_first_task_'Dogs_vs_Cats'.ipynb ├── Numpy ├── 1. Numpy Foundation.ipynb ├── 2. NumpyArraysAndVectorizedComputation.ipynb └── 3. Numpy IteratingOverArray.ipynb ├── README-JP.md ├── README.md └── Tutorials ├── Customers’ tweets classification ├── Customers’ tweets classification.ipynb ├── __pycache__ │ └── utils.cpython-36.pyc ├── data │ └── Airline-Sentiment-2-w-AA.csv └── utils.py └── Linear Regression on Boston Housing Dataset.ipynb /Books/DeepLearningwithPython - Jason Brownlee/Chapter 10. Project_Multiclass Classification Of Flower Species.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yui-py/How-to-learn-Machine-Learning/HEAD/Books/DeepLearningwithPython - Jason Brownlee/Chapter 10. 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