Stochastic Gradient Descent Classifier - Machine Learning # 2

☕️ Buy me a coffee: https://paypal.me/donationlink240 🙏🏻 Support me on Patreon:   / ahmadbazzi   📚About This is the second lecture of the series entitled “Machine Learning with TensorFlow & Scikit-learn”, we will introduce what Binary Classification is along with the Stochastic Gradient Descent classifier (with its penalties and losses). This lecture is outlined as follows: 00:00:00 Introduction 00:01:20 MNIST Database 00:02:59 Setting JUPYTER notebook 00:04:05 Installing sklearn 00:04:45 Fetching MNIST 00:06:23 What is NumPY ? 00:06:58 Analyzing MNIST 00:11:10 Visualizing MNIST images 00:11:37 MATPLOTLIB 00:13:03 Grayscale images 00:14:32 The Train/Test Split 00:15:36 Permutation-sensitivity 00:16:47 Binary Classification 00:18:54 Stochastic Gradient Descent Classifier 00:23:18 Stochastic Gradient Descent Classifier with Quadratic Loss 00:23:30 Stochastic Gradient Descent Classifier with Logistic Loss 00:24:57 Stochastic Gradient Descent Classifier with Hinge Loss 00:28:38 Stochastic Gradient Descent Classifier with ϵ-insensitive Loss 00:30:22 Stochastic Gradient Descent Classifier with ℓ-2 Penalty 00:30:40 Stochastic Gradient Descent Classifier with ℓ-1 Penalty 00:30:55 Stochastic Gradient Descent Classifier with Elastic Net Penalty 00:31:49 Math Behind Stochastic Gradient Descent Classifier 00:37:28 SGD Classifier with sklearn 00:40:26 Cross Validation 00:42:26 Outro ============================================================ Lecture 1: Introduction    • Introduction - Machine Learning # 1   ============================================================ Instructor: Dr. Ahmad Bazzi IG:   / drahmadbazzi   Browser: https://www.google.com/chrome/ ============================================================ Credits: Google https://www.google.com/ Google Photos https://www.google.com/photos/about/ TensorFlow https://www.tensorflow.org/ scikit-learn https://scikit-learn.org/stable/ Numpy https://numpy.org/ Microsoft OneNote https://www.onenote.com/signin?wdorig... Python https://www.python.org/ ============================================================ References: [1] Géron, Aurélien. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O'Reilly Media, 2019. https://www.amazon.com/Hands-Machine-... [2] Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006. https://www.amazon.com/Pattern-Recogn... [3] Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. The elements of statistical learning. Vol. 1. No. 10. New York: Springer series in statistics, 2001. https://www.amazon.com/Elements-Stati... [4] Burkov, Andriy. The hundred-page machine learning book. Quebec City, Can.: Andriy Burkov, 2019. https://www.amazon.com/Hundred-Page-M... [5] Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016. https://www.amazon.com/Deep-Learning-... [6] Chollet, Francois. Deep Learning mit Python und Keras: Das Praxis-Handbuch vom Entwickler der Keras-Bibliothek. MITP-Verlags GmbH & Co. KG, 2018. https://www.amazon.com/Deep-Learning-... [7] De Prado, Marcos Lopez. Advances in financial machine learning. John Wiley & Sons, 2018. https://www.amazon.com/Advances-Finan... [8] Duda, Richard O., Peter E. Hart, and David G. Stork. Pattern classification. John Wiley & Sons, 2012. https://www.amazon.com/Pattern-Classi... [9] Lapan, Maxim. Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. Packt Publishing Ltd, 2018. https://www.amazon.com/Deep-Reinforce... [10] Bonaccorso, Giuseppe. Machine Learning Algorithms: Popular algorithms for data science and machine learning. Packt Publishing Ltd, 2018. https://www.amazon.com/Machine-Learni... [11] Deisenroth, Marc Peter, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for machine learning. Cambridge University Press, 2020. https://mml-book.github.io/book/mml-b... [12] Krollner, Bjoern, Bruce J. Vanstone, and Gavin R. Finnie. "Financial time series forecasting with machine learning techniques: a survey." ESANN. 2010. #MachineLearning #TensorFlow #MachineLearningTutorial