Enroll Course: https://www.udemy.com/course/machine-learning-deep-learning-model-deployment/
If you’re venturing into the world of Machine Learning (ML) and Deep Learning (DL) and want to go beyond just building models, the Udemy course “Machine Learning Deep Learning Model Deployment” is an exceptional resource. This course is specially designed for beginners with no prior experience, making it accessible and highly practical.
The course covers a wide range of deployment techniques, from deploying models locally and on Google Colab to cloud-based solutions like Google Cloud. You’ll learn to create REST APIs using Python Flask, deploy models on cloud servers, and even explore serverless options with Cloud Functions. Notably, it dives into deploying popular frameworks like TensorFlow, Keras, and PyTorch, including converting models with ONNX.
One of the highlights is the hands-on approach, where you get to build and deploy models such as text classifiers for Twitter sentiment analysis, and even deploy TensorFlow.js models for web applications. The course also touches on tracking experiments with MLflow, a crucial skill for managing ML projects.
Additionally, the course introduces cutting-edge topics like Generative AI, GPT models, and creating chatbots with OpenAI API. This broad range of topics ensures learners are well-equipped to handle real-world deployment scenarios.
I highly recommend this course for anyone looking to bridge the gap between model development and production deployment. Whether you’re a beginner or someone aiming to enhance your deployment skills, this course offers practical insights and step-by-step guidance to succeed in deploying ML and DL models efficiently.
Enroll Course: https://www.udemy.com/course/machine-learning-deep-learning-model-deployment/