Share Description
This course is a detailed guide that talks about the concept of building and learning about automotive systems. It is designed for both beginners and experts in the field of computer vision and teaches you how to create automotive algorithms which help power the self-driving cars. This course covers the important techniques and frameworks while utilising Keras, a necessary library in Python that guides you on how to build and train neural networks. With the use of Keras, you will also learn the building and training techniques of basic perceptron models and CNNs. This course aims to teach you how to simulate a functional self-driving car while learning vision algorithms.
Topics Covered:
- Course Introduction: Get introduced to the course and gain some insights about the expert who will teach you the essentials.
- Installation: Start by installing the Anaconda Distribution for both Mac and Windows along with the Atom text editor.
- Python Crash Course: Learn the concepts of Python Crash Course like data types, arithmetic operations, variables and lists.
- Functions: Come across its different functions like scope, doc strings and lambda and higher-order functions.
- NumPy Crash Course: Get familiar with the concepts of this crash course like reshaping, stacking, matrix multiplication and arrays.
- Computer Vision: Start by learning how to load an image and smooth an image and later learn how to save your file.
- Perceptron: Understand what machine learning is and its concepts like weights, linear model, source code and cross entropy
- Keras: Learn the basic framework of Keras and know what its models, predictions and starter codes are.
- And Many More Topics..
Who Will Benefit?
- Data Scientists: Individuals who are eager to learn about Keran, CNN and self-driving cars along with their automotive algorithms.
- Students In The Tech Field: Students who want to learn about Python programming, perceptron, variables and CNN networking.
- AI Engineers: Engineers who want to learn the basics to further apply the skills to complex problems and projects.
Why Choose This Course?
By choosing this course, you will have in-depth learning about building a self-driving car simulation and learn the theory of CNN. This course benefits you by letting you apply several machine learning techniques to difficult automotive algorithms and letting you simulate the power of autonomous vehicles. You will gain detailed learning about concepts like identifying lane lines on a road, computer vision, convolutional neural networks and deep learning models, all using the most important Python library, Keras. By the end of this course, you will be able to classify different types of traffic signs and perform visual recognition tasks.
