course 1 of 5 from Deep Tensor specialization
What you'll learn:
- Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
- Machine Learning Algorithms
- Learn to use TensorFlow 2.0 for Deep Learning
- TensorFlow 1.x VS TensorFlow 2
- Image Recognition
- Computer Vision
- Convolutional Neural Network
- Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance
- Learn how to train network weights and biases and select the proper transfer functions.
- Learn how to Create your own data-set
- Retrain a pretrained model
- YOLO object detector
- Apply Convolutional Neural Networks to classify images.
- build Deep Learning Algorithms from Scratch in Python Using NumPy and TensorFlow
DL continues to take powerful steps to become a part of almost any software in the future. DL is one of the most popular research areas of machine learning. What makes it so popular is the exciting applications of recent times. Nowadays, improvement in machine learning provides the ability to determine what an object in a picture does.
this is the course one from our specialization deep tensor, in this course we will going to take multiple real-world projects using Tensorflow 2
by the end of this course, you will feel comfortable and confident after learning those projects using python and deep learning, so yeah what you are waiting for let's begin this journey together and I hope to enjoy the ride thanks.