In this video, we will look at the concluding remarks of the course and recap what we learned through the course, briefly.
<
br/>
This clip is from the chapter "Conclusion" of the series "Machine Learning: Random Forest with Python...

In this video, you will learn to implement the accuracy method to help determine our model's performance.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with Python...

Here, we will determine the best split at any decision node where information is maximum and split into two branches, true and false.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning:...

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

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

Before creating a decision tree, we will first learn to import our dataset using Pandas.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with Python from...

Let's quickly implement Random Forest using the sklearn Random Forest model to tune the model's performance according to the project.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning:...

In a machine, it understands values in the form of numbers. You will learn how to convert non-numeric data to numeric without changing the feature of the value.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of...

In the second part of the data cleaning process, we will look at an outlier in detail and learn how to correct or remove the outlier.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning:...

Let's look at the first step involved in the data cleaning process, which is filling or removing missing values from a dataset.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning:...

Previously, you learned how to read a dataset; now, we will look at manipulating the data and using a sample dataset in our code.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning:...

This is a continuation of the previous lesson, and here we will look at conditionally selecting values from a dataset.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest...

In this video, we will discuss our final project, which classifies the titanic dataset using Random Forest.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with Python...

In this video, we will look at the benefits and limitations of Random Forest and the complexities involved in decision-making using Random Forest.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series...

We will understand what a decision tree is and create a decision tree and get a prediction result from the decision tree.
<
br/>
This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random...

In this video, we will implement the ability to delete ideas from the list.
<
br/>
This clip is from the chapter "RandomIdeas Project - Webpack Frontend (Bonus Project)" of the series "Modern JavaScript from the Beginning".In this...

This video explains Chart.js, a popular charting library for JavaScript. It makes what would be a difficult combination of styling, layout, and data positioning into an easy to manage ordeal, saving developers loads of time in creating...

In this lab assignment video, we will be testing your knowledge of caching in Python applications by asking you to implement a caching mechanism.
<
br/>
This clip is from the chapter "Google App Engine - For Serverless Applications"...

In this video, we walk you through the process of deploying a Python application that interacts with BigQuery, showing you how to set up and configure your BigQuery project, how to create a basic Flask application that integrates with...

This video demonstrates how to design a recurrent neural network or RNN.
<
br/>
This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with...

This video demonstrates a deeper CNN, where you will build a much bigger number of trainable parameters.
<
br/>
This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This...

This video demonstrates the architecture and how to carry out the code using TensorFlow in collab and building a convolutional neural network.
<
br/>
This clip is from the chapter "Convolutional Neural Networks" of the series...

This video demonstrates functional API versus sequential API.
<
br/>
This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural networks where...

This video demonstrates how to use Keras TensorFlow as API to essentially design and craft the neural network architecture.
<
br/>
This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural...