Embark on a comprehensive journey through 14 hours of hands-on machine learning projects in Python, covering a wide range of applications from financial analysis to computer vision. Learn to develop and deploy ML models for real-world scenarios, including customer subscription prediction, cancer detection, house price forecasting, and image classification. Master essential techniques such as regression, neural networks, and convolutional neural networks (CNNs) while gaining practical experience with popular frameworks like TensorFlow and Keras. Explore deployment strategies using Flask, Heroku, and AWS EC2, and dive into advanced topics like transfer learning with pre-trained models such as VGG16, ResNet50, and InceptionV3. Build exciting computer vision applications, including face detection, car detection, and live video processing. By the end of this course, you'll have the skills to create, train, evaluate, and deploy machine learning models for various industries, including finance, healthcare, real estate, and agriculture.
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