6.10. Model Parameters and Hyperparameters | Weights & Bias | Learning Rate & Epochs
🚀 Complete Machine Learning & Generative AI Course - Hands-on • Real-World Projects • Production Deployment: 👉 https://linktr.ee/siddhardhan In this video, I explained about Model Parameters and Hyperparameters in Machine Learning. weights and Bias are the two important model parameters. Learning rate and Epochs are the two main Hyperparameters. All presentation files for the Machine Learning course as PDF for as low as â‚ą200 (INR): Drop a mail to [email protected] Linear Regression video:    • Video  Loss Function video:    • 6.8. Loss Function in Machine Learning  Enroll at One Neuron to learn from 100 courses in one subscription with 5% discount: https://courses.ineuron.ai/neurons/Te... Machine Learning Course with Python Playlist:    • Machine Learning Course With Python  Machine Learning Projects Playlist:    • Machine Learning Projects  Hello everyone! I am setting up a donation campaign for my YouTube Channel. If you like my videos and wish to support me financially, you can donate through the following means: From India 👉 UPI ID : siddhardhselvam2317@oksbi Outside of India? 👉 Paypal id: [email protected] (No donation is small. Every penny counts) Thanks in advance! Let's build a Community of Machine Learning experts! Kindly Subscribe here👉 https://tinyurl.com/md0gjbis I am making a "Hands-on Machine Learning Course with Python" in YouTube. I'll be posting 3 videos per week: Monday Evening; Wednesday Evening; Friday Evening. Download the Course Curriculum File from here: https://drive.google.com/file/d/17i0c... LinkedIn:   / siddhardhan-s-741652207  Telegram Group: https://t.me/siddhardhan Facebook group: https://www.facebook.com/groups/49085... Getting error in any of the codes that I have explained? Mail the details of the error to: [email protected] Instagram:   / siddhardhan23 Â
6.11. Gradient Descent in Machine Learning
Hands-On Hyperparameter Tuning with Scikit-Learn: Tips and Tricks
8.3. Hyperparameter Tuning - GridSearchCV and RandomizedSearchCV
6.1. What is a Machine Learning Model?
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Model Predictive Control
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5.3.3. Random Variables and its types | Discrete Random Variables | Continuous Random Variables
8.8. Precision, Recall, F1 score | Model Evaluation
8.7. Accuracy Score and Confusion Matrix - Concept & Python implementation | Model Evaluation in ML
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5.2.5. Population and Sample | Sampling techniques | Statistics for Machine Learning
