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Activation functions (step, sigmoid, tanh, relu, leaky relu ) are very important in building a non linear model for a given problem. In this video we will cover different activation functions that are used while building a neural network. We will discuss these functions with their pros and cons, 1) Step 2) Sigmoid 3) tanh 4) ReLU (rectified linear unit) 5) Leaky ReLU We will also write python code to implement these functions and see how they behave for sample inputes. Github link for code in this tutorial: : https://github.com/codebasics/deep-le... Do you want to learn technology from me? Check https://codebasics.io/?utm_source=des... for my affordable video courses. 🔖 Hashtags 🔖 #activationfunction #activationfunctionneuralnetwork #neuralnetwork #deeplearning Next video: • Derivatives | Deep Learning Tutorial 9 (Te... Previous video: • Neural Network For Handwritten Digits Clas... Deep learning playlist: • Deep Learning With Tensorflow 2.0, Keras a... Machine learning playlist : https://www.youtube.com/playlist?list... Prerequisites for this series: 1: Python tutorials (first 16 videos): https://www.youtube.com/playlist?list... 2: Pandas tutorials(first 8 videos): • Pandas Tutorial (Data Analysis In Python) 3: Machine learning playlist (first 16 videos): https://www.youtube.com/playlist?list... 🌎 My Website For Video Courses: https://codebasics.io/?utm_source=des... Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. #️⃣ Social Media #️⃣ 🔗 Discord: / discord 📸 Dhaval's Personal Instagram: / dhavalsays 📸 Instagram: / codebasicshub 🔊 Facebook: / codebasicshub 📝 Linkedin (Personal): / dhavalsays 📝 Linkedin (Codebasics): / codebasics 📱 Twitter: / codebasicshub 🔗 Patreon: https://www.patreon.com/codebasics?fa...