Linear Regression | Machine Learning # 7

☕️ Buy me a coffee: https://paypal.me/donationlink240 🙏🏻 Support me on Patreon:   / ahmadbazzi   📚About This lecture talks simply talks about Linear Regression. The lecture also shows how to get the job done on Python and with the help of sklearn. We've got ‪@WhatsAI‬ as a host on this lecture. Louis of ‪@WhatsAI‬ helps me explain what Linear Regression is. Please help me in welcoming Louis. ⏲Outline⏲ 00:00 Introduction 01:30 What is Linear Regression ? 04:26 GDP vs Life Satisfaction Example 09:15 Features & Model Parameters 12:23 How do we train it ? 16:28 Python: The manual way 20:28 Python: The sklearn way 21:46 Computational Complexity 26:12 Outro 🔴 Subscribe for more videos on Machine Learning and Python. 👍 Smash that like button, in case you find this tutorial useful. 👁‍🗨 Speak up and comment, I am all ears. ============================================================ Lecture 1: Introduction    • Introduction - Machine Learning # 1   Lecture 2: Binary Classification & SGD Classifier    • Stochastic Gradient Descent Classifier - M...   Lecture 3: Performance Measures    • Performance Measures - Machine Learning # 3   Lecture 4: Multiclass classification & Cross Validation    • Multiclass classification & Cross Validati...   Lecture 5: Gradient Descent    • Gradient Descent - Machine Learning # 5   Lecture 6: Multilabel and Multioutput Classification    • Multilabel and Multioutput Classification ...   ============================================================ 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