Deep Learning Masterclass with TensorFlow 2 Over 15 Projects
Master Deep Learning with TensorFlow 2 with Computer Vision,Natural Language Processing, Sound Recognition & Deployment
In this course, we shall look at core Deep Learning concepts and apply our knowledge to solve real world problems in Computer Vision and Natural Language Processing using the Python Programming Language and TensorFlow 2. We shall explain core Machine Learning topics like Linear Regression, Logistic Regression, Multi-class classification and Neural Networks. If you’ve gotten to this point, it means you are interested in mastering Deep Learning For Computer Vision and Deep Learning, using your skills to solve practical problems.
Best Seller Course: Deep Learning Prerequisites: Logistic Regression in Python
What you’ll learn
- Introductory Python, to more advanced concepts like Object Oriented Programming, decorators, generators, and even specialized libraries like Numpy & Matplotlib
- Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
- Linear Regression, Logistic Regression and Neural Networks built from scratch.
- TensorFlow installation, Basics and training neural networks with TensorFlow 2.
- Convolutional Neural Networks, Modern ConvNets, training object recognition models with TensorFlow 2.
- Breast Cancer detection, people counting, object detection with yolo and image segmentation
- Generative Adversarial neural networks from scratch and image generation
- Recurrent Neural Networks, Modern RNNs, training sentiment analysis models with TensorFlow 2.
- Neural Machine Translation, Question Answering, Image Captioning, Sentiment Analysis, Speech recognition
- Deploying a Deep Learning Model with Google Cloud Function.
You May Also Need This Course: Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs
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