You’re going to learn the most popular library to build networks and machine learning algorithms.
In this hands-on, practical course, you will be working your way through with Python, Tensorflow, and Jupyter notebooks.
What you will learn:
•Basics of Tensorflow
•Artificial Neurons
•Feed Forward Neural Networks
•Activations and Softmax Output
•Gradient Descent
•Backpropagation
•Loss Function
•MSE
•Model Optimization
•Cross-Entropy
•Linear Regression
•Logistic Regression
•Convolutional Neural Networks (with examples)
•Text and Sequence Data
•Recurrent Neural Networks (with examples)
•Neural Style Transfer (in progress)
Transfer Learning, TensorFlow Object detection, Classification, Yolo object detection, real time projects much more..!!
3.7
★★★★★ 3.7/5
23,885 students