Curated Video
Deep Learning - Artificial Neural Networks with Tensorflow - Code Preparation (Classification Theory)
In this video, we will take a crash course in linear classification for TensorFlow 2.0. This clip is from the chapter "Machine Learning and Neurons" of the series "Deep Learning - Artificial Neural Networks with TensorFlow".In this...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - Preparation and Evaluation
In this video, you will learn how to train our LeNet model. This clip is from the chapter "LeNet Architecture in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In this section, you will learn how to...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - Writing a Deep Neural Network
In this video, you will learn how to write a deep neural network. This clip is from the chapter "Creating Deep Neural Networks in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In this section, we...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - Building the First Neural Network
In this video, you will learn how to build your first neural network. This clip is from the chapter "Creating Deep Neural Networks in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In this section,...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - AutoGrad in a Loop
In this video, you will learn to implement the AutoGrad function in a loop. This clip is from the chapter "AutoGrad in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In this section, we will have a...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - AutoGrad in PyTorch
In this video, you will learn what is AutoGrad in PyTorch. This clip is from the chapter "AutoGrad in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In this section, we will have a look at AutoGrad...
Curated Video
Deep Learning - Computer Vision for Beginners Using PyTorch - Why Is PyTorch Powerful?
In this video, we will look at a quick demo and understand why PyTorch is powerful. This clip is from the chapter "Welcome Aboard" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".Welcome to the course! This is...
Curated Video
Recommender Systems: An Applied Approach using Deep Learning - Compute Loss
Here, we will look at the next step of training our model: the compute loss function. This clip is from the chapter "Project Amazon Product Recommendation System" of the series "Recommender Systems: An Applied Approach Using Deep...
Curated Video
Can Images Classify Themselves? | Self-Organization and Neural Cellular Automata
Can Images Classify Themselves? | Self-Organization and Neural Cellular Automata
Curated Video
How Do Physics-Informed Neural Networks Work?
Can physics help up develop better neural networks?
APMonitor
Logistic Regression from Scratch
Logistic regression is a machine learning algorithm for classification. In this algorithm, the probabilities describing the possible outcomes of a single trial are modeled using a logistic function. Logistic regression makes a binary...
Packt
Develop an AI system to solve a real-world problem : Building Artificial Neural Networks
From the section: Predicting Sales with Supervised Learning. In this section, learners will use their first machine learning techniques, including Support Vector Machines and Artificial Neural Networks. These techniques will be applied...
APMonitor
Convolutional Neural Network Image Classification
Deep Learning (DL) is a subset of Machine Learning that uses Neural Network inspired architecture to make predictions. Convolutional Neural Networks (CNN) are a type of DL model that is effective in learning patterns in 2-dimensional...
APMonitor
Data Science 🐍 Features
Features are input values to regression or classification models. The features are inputs and labels are the measured outcomes. Classification predicts discrete labels (outcomes) such as yes/no, True/False, or any number of discrete...
Fun Robotics
Project Neural Network
Design a Neural Network to classify handwritten digits using Keras and TensorFlow
APMonitor
LSTM Replaces PID Control
The purpose of this exercise is to automate a temperature control process with an LSTM network. The LSTM network is trained from a PID (Proportional Integral Derivative) controller or a Model Predictive Controller (MPC). LSTM (Long Short...
APMonitor
Split Data for Machine Learning
Splitting data ensures that there are independent sets for training, testing, and validation. Data can be divided into sequential blocks where the order is preserved (e.g. time series) or with random selection (shuffle). Cross-validation...
Curated Video
Create a computer vision system using decision tree algorithms to solve a real-world problem : Example 1 - Build Multi-layer perceptron for binary classification
From the section: Artificial Neural Networks. In this section, we’ll learn about ANN. Artificial Neural Networks: Example 1 - Build Multi-layer perceptron for binary classification
Curated Video
Create a computer vision system using decision tree algorithms to solve a real-world problem : Building Deep Neural Networks with Keras, Normalization, and One-Hot Encoding.
From the section: Deep Learning and Tensorflow: Part 1. In this section, we’ll talk about what Deep Learning is, and how TensorFlow works at a low level. Deep Learning and Tensorflow: Part 1: Building Deep Neural Networks with Keras,...
Curated Video
Use a real-life example of an AI system to discuss some impacts of cyber attacks : Attacks on Classification and How They Work
From the section: Security Test Using Adversarial Attack. In this section, you will test any AI system against the latest attacks with the help of simple tools. The aim of this video is to describe why adversarial attacks occur and how...
Curated Video
Create a computer vision system using decision tree algorithms to solve a real-world problem : Code to Train a perceptron for binary classification
From the section: Artificial Neural Networks. In this section, we’ll learn about ANN. Artificial Neural Networks: Code to Train a perceptron for binary classification
Packt
Explain the negative impacts of artificial intelligence systems on society : CW Attack Practical Configuration
From the section: Compare Various Attacks. In this section, you will learn the most important metrics to compare various attacks. Now, you will dive deeper into various adversarial attacks from the white-box category. You will see how...
APMonitor
Machine Learning for Engineers Course Intro
Machine Learning, Digitalization, and Data Science are transforming industries with new automation and decision support. This course focuses on the foundations of machine learning with application to engineering.
Curated Video
Practical Data Science using Python - Linear Regression - Training and Cost Function
This video explains linear regression - training and cost function. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.