Book Image

Python Artificial Intelligence Projects for Beginners [Video]

By : Dr. Joshua Eckroth
Book Image

Python Artificial Intelligence Projects for Beginners [Video]

By: Dr. Joshua Eckroth

Overview of this book

<p><span id="description" class="sugar_field">Artificial Intelligence (AI)is one of the hottest fields in computer science right now and has taken the world by storm as a major field of research and development. Python has surfaced as a dominate language in AI/ML programming because of its simplicity and flexibility, as well as its great support for open source libraries such as Scikit-learn and Keras.<br /> Built for rookie AI enthusiasts across eight realistic projects, this course covers modern techniques that make up the world of AI. You’ll start with your first project that covers decision trees for classifying data using Scikit-learn libraries. Next, you will build a classifier using random forests. Then you will learn about text processing techniques and practice with bag-of-words and word2vec models. Further, you will be introduced to deep learning and neural networks and practice with projects that make use of Keras and convolutional neural networks. </span></p> <p><span id="description" class="sugar_field">By the end of this video course, you will be confident to build your own AI projects with Python and be ready to take on more advanced content as you go ahead.</span></p> <h2><span class="sugar_field">Style and Approach</span></h2> <p><span class="sugar_field"><span id="trade_selling_points_c" class="sugar_field"><span id="tagline_c" class="sugar_field"><span id="trade_selling_points_c" class="sugar_field">Built for rookie AI enthusiasts across eight realistic projects, this course covers modern techniques that make up the world of Artificial Intelligence.</span></span></span></span></p>
Table of Contents (3 chapters)
Chapter 2
Applications for Comment Classification
Content Locked
Section 2
Detecting YouTube Comment Spam with Bag of Words and Random Forests
In this video, we will see how we can identify spam comments on a website. We look at a YouTube spam dataset to practice with bag-of-words and random forests to solve this problem. - Examine the dataset - Write code to produce a bag-of-words model - Use a random forest for the classifier and evaluate its performance