100 Days of Deep Learning - Handwritten Digit Classification using ANN | MNIST Dataset

Handwritten Digit Classification using Artificial Neural Networks (ANN) involves training a model to recognize and classify handwritten digits, typically from 0 to 9. The ANN learns patterns from labeled datasets, allowing it to generalize and accurately identify handwritten digits in unseen data. Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Link - https://colab.research.google.com/drive/1SqETl3Zi1EEesdJfEv6_QimB-M-YjKGx?usp=sharing ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! ✨ Hashtags✨ #MachineLearning #ImageRecognition #HandwrittenDigits #NeuralNetworks #DataScience #classificationmodel ⌚Time Stamps⌚ 00:00 - Intro 01:40 - MNIST Dataset 05:20 - Code Demo 25:28 - Accuracy Plot 28:06 - Outro