Deep Learning in TensorFlow #1 L3 - NumPy Array Creation

Published: 05 November 2021
on channel: eMaster Class Academy

399

⭐️About this Course
This Deep Learning in TensorFlow Specialization is a foundational program that will help you understand the principles and Python code of Machine Learning and Deep Learning and prepare you to participate in the development of leading-edge AI and data scientist technology.

In this Specialization, you will build and train neural network architectures with some hands-on project, such as Vanilla Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and learn the advance techniques on how to make them better with strategies.

🌟🌟🌟 Earn a Certificate [MEMBERS only]
When you finish every course and complete the hands-on project and a final project assessment, you'll earn a Certificate that you can share with prospective employers.

============================================================================
⭐️⭐️⭐️Join this channel to get access to Members-only resources: / @emasterclassacademy

⭐️⭐️⭐️Support FREE content: https://www.buymeacoffee.com/eMasterC...
============================================================================

What you will learn from this course:
Course 1 Numpy Basics
- Introduction to Tensors for Deep Learning with NumPy
- NumPy Structure
- NumPy Properties & Attributes
- NumPy Array Creation
- NumPy Indexing and Slicing
- NumPy Shape Manipulation
- NumPy Element-wise VS Broadcasting
- NumPy Aggregate and Statistical Functions
- NumPy Dot Product and Matrix Multiplication

Course 2 Neural Networks in TensorFlow
- A Gentle Introduction of AI, ML and NN
- Logistic Regression
- From Logistic Regression to Neural Network
- Build your first Neural Network
Hands-on Project - Image Classification

Course 3 Neural Networks in TensorFlow - Advanced Techniques
- Introduction & Sequential Model
- Sequential Model - Attributes
- Sequential Model - Save and load models
- Sequential Model - Compile()
- Frequently Used Optimizers
- Frequently Used Loss Functions
- Frequently Used Metrics
- Sequential Model - Fit()
- Usage of Returns
- Usage of Callbacks
- ModelCheckPoint
- TensorBoard
- EarlyStopping
- Usage of Batch Size
- Sequential Model - Evaluate()
- Sequential Model - Predict()

Course 4 Convolutional Neural Networks in TensorFlow
- Introduction & Basic Architecture
- Build your first Convolutional Neural Network
- Convolutional Layer
- Kernel, Strides, Padding
- Activation
- Pooling Layer
- Maximum Pooling
- Average Pooling
- Flatten & Dense Layer

Course 5 Recurrent Neural Networks in TensorFlow
- Introduction
- Mathematical Representations
- Build your first Recurrent Neural Network
- Recurrent Neural Networks
- Vanishing and Exploding Gradients
- Solutions
- Long Short-Term Memory (LSTM) Networks
- Introduction
- Core Concept of LSTMs
- How LSTMs work
- Summary
Hands-on Project - LSTM model for Image Classification

Course 6 Keras Functional API
- Introduction
- Build a Neural Network with Functional API
- Features
- Use the same graph of layers to define multiple models
- Callable model
- Manipulate complex graph topologies
- Shared layers
- Extract and reuse nodes
Hands-on Project - ResNet model for Image Classification

Watch video Deep Learning in TensorFlow #1 L3 - NumPy Array Creation online, duration hours minute second in high quality that is uploaded to the channel eMaster Class Academy 05 November 2021. Share the link to the video on social media so that your subscribers and friends will also watch this video. This video clip has been viewed 399 times and liked it 12 visitors.

203