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Updated in [October 07th, 2023]
What does this course tell?
(Please note that the following overview content is from the original platform)
In this course we will start from the basics and will learn all concepts of machine learning self-driving car python and computer vision We will build multiple projects including self-driving car in this course We will learn all these things by practically building projects I hope you will enjoy course and will learn lot of thingsour main topics will beComputer VisionSelf-driving CarsMachine LearninigPythonDeep LearningNeural NetworksOpenCVWho this course is for:Anyone interested in Self Driving CarsMachine learningStudents who have at least high school knowledge in math and who want to start learning Machine LearningAny intermediate level people who know the basics of machine learning including the classical algorithms like linear regression or logistic regression but who want to learn more about it and explore all the different fields of Machine LearningAny people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasetsAny students in college who want to start a career in Data ScienceAny data analysts who want to level up in Machine LearningAny people who are not satisfied with their job and who want to become a Data ScientistAny people who want to create added value to their business by using powerful Machine Learning tools
We considered the value of this course from many aspects, and finally summarized it for you from two aspects: skills and knowledge, and the people who benefit from it:
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What skills and knowledge will you acquire during this course?
By taking this course, you will acquire the following skills and knowledge:
1. Computer Vision: You will learn the fundamentals of computer vision, including image processing, feature extraction, and object detection. You will also gain hands-on experience in implementing computer vision algorithms using Python and OpenCV.
2. Self-driving Cars: You will understand the principles and techniques behind self-driving cars, including perception, decision-making, and control. You will build projects that simulate self-driving car behavior and learn how to train models to make autonomous driving decisions.
3. Machine Learning: You will learn the foundations of machine learning, including supervised and unsupervised learning algorithms. You will explore various machine learning techniques such as regression, classification, clustering, and dimensionality reduction.
4. Python: You will gain proficiency in Python programming language, which is widely used in the field of machine learning and computer vision. You will learn how to write efficient and scalable code to implement machine learning algorithms and build projects.
5. Deep Learning: You will delve into deep learning, a subfield of machine learning that focuses on training neural networks. You will learn about different types of neural networks, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and understand how to apply them to solve complex problems.
6. Neural Networks: You will gain a deep understanding of neural networks, their architecture, and how they learn from data. You will learn how to design and train neural networks for various tasks, including image classification, object detection, and autonomous driving.
7. OpenCV: You will become proficient in using OpenCV, a popular computer vision library, to perform various image processing tasks. You will learn how to manipulate images, detect objects, and extract features using OpenCV functions.
Who will benefit from this course?
This course is beneficial for individuals with various interests and specific professions.
1. Students interested in self-driving cars: This course provides a comprehensive understanding of machine learning, computer vision, and deep learning techniques used in self-driving cars. It is suitable for students who want to pursue a career in autonomous vehicle technology.
2. Machine learning enthusiasts: Individuals with a basic understanding of machine learning algorithms, such as linear regression or logistic regression, can benefit from this course. It offers an opportunity to explore different fields of machine learning and expand their knowledge.
3. Data analysts looking to level up in machine learning: For data analysts who want to enhance their skills in machine learning, this course offers practical projects and hands-on experience. It helps them apply machine learning techniques to datasets and gain valuable insights.
4. Professionals interested in data science: Individuals who are not satisfied with their current job and aspire to become data scientists can benefit from this course. It provides a solid foundation in machine learning, Python programming, and computer vision, which are essential skills in the field of data science.
5. Business professionals seeking to create added value: This course equips individuals with powerful machine learning tools that can be applied to their business. It enables them to leverage data and extract valuable insights, ultimately enhancing their business operations and decision-making processes.
Course Syllabus
Machine Learning
Python
Computer Vision
Small Self Driving Car Project
Data Preprocessing
Supervised Learning : Regression Models
Other models
Unsupervised Learning
Deep Learning
Project 1 - Real estate price prediction
Project 2