In this video, we will see the recommended order of taking the lessons offered in this learning program, the logical progression of the course, and the optimal order to take the courses to maximize our learning and understanding of the...

In this video, we will define columns for questioning and determine how much information can be gained by splitting a column. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with...

Like all dataset characteristics, we will look at the impurities in a dataset and how they should be minimum in a good dataset. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest...

In this video, you will learn about the concept of factorials in mathematics and how to calculate them using JavaScript. A factorial is a mathematical function that represents the product of all positive integers from 1 up to a given...

This video explains VGG16 which is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition". This clip...

This video explains logistic regression and specifically if the target here is discrete or binary. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...

Explore the real chances of winning the lottery and the intricacies of sports betting. This video breaks down the probabilities, the science of randomness, and the strategies players use in hopes of maximizing their winnings. Featuring...

In this video, you will learn about ReLU, SoftMax, and Cross Entropy. This clip is from the chapter "Applying Deep Learning" of the series "Deep Learning - Crash Course 2023".In this section, you will learn how to implement deep learning...

In this video, we will have an in-depth look at different activation functions provided in the TensorFlow library using Google Colab. This clip is from the chapter "Activation Functions in Deep Learning Neural Networks" of the series...

In this video, we will talk about certain events and understand why we require entropy loss. This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about...

In this video, you will learn about the probability distribution table. This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, you will learn about different types of random variables. This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, we will understand why a random variable is important. This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, we will be introduced to probability and random variables. This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, we will be introduced to Sigmoid Neuron. This clip is from the chapter "Sigmoid Neuron" of the series "Deep Learning - Crash Course 2023".In this section, we will begin our journey with Sigmoid Neuron.

In this video, you will learn about categorical cross entropy, which is used in multiclass classification. This clip is from the chapter "In-Depth: Loss Functions" of the series "Deep Learning - Artificial Neural Networks with...

In this video, you will learn about binary cross entropy, which is the correct loss function to use for binary classification. This clip is from the chapter "In-Depth: Loss Functions" of the series "Deep Learning - Artificial Neural...

In this video, you will learn about multiclass classification. This clip is from the chapter "Feedforward Artificial Neural Networks" of the series "Deep Learning - Artificial Neural Networks with TensorFlow".In this section, we will...

This video explains threat modeling and identifying threats. This clip is from the chapter "Security and Risk Management" of the series "CISSP Crash Course".This section explains domain 1, which focuses on security and risk management.

In this video, we will summarize what we have learnt about SciPy and understand where it can be applied. This clip is from the chapter "SciPy" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this...

In this video, we will be introduced to SciPy and understand this section’s learning objective. This clip is from the chapter "SciPy" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this section,...

In this video, we will have a quick overview of Matplotlib that is used to visualize data and see what we are going to cover in this section. This clip is from the chapter "Matplotlib" of the series "Data Science Prerequisites - NumPy,...

In this lecture, we will identify if the content is generated by AI or written by a human. We will discuss the characteristics and patterns of language that may indicate the use of AI-generated content and how to distinguish it from...

Write a program to generate random math problems and automatically grade them.