Explanation
In this course, we aim to specialize in artificial intelligence by working on 7 Machine Learning Projects and 7 Deep Learning Projects (14 AI Projects in total) at different levels (easy – medium – hard). Before starting the course, you should have basic Python knowledge. Our goal in this course is to turn real-life problems into projects and then solve them using the latest versions of artificial intelligence algorithms (machine learning algorithms and deep learning algorithms) and Python. We will implement some of our projects using machine learning and some using deep learning algorithms.
This way, you will have an overview of artificial intelligence. By completing our course projects, you will gain a clear understanding of the basic working principles of Machine Learning software and Deep Learning Algorithms and the differences between them. In our course, we will use well-known datasets that are widely used in higher education on Machine Learning as well as custom datasets. By doing our projects, you will learn the concepts of artificial intelligence and you will also learn about this popular data. After completing the course, you will be able to easily come up with solutions to problems you may encounter in real life. For Machine Learning projects we will use Scikit-Learn Python Library. In our Deep Learning projects we will be using Tensorflow and Keras libraries.
What will you learn?
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You will practice Machine Learning and Deep Learning Algorithms by solving real-life problems using the latest version of libraries (July 2021)
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How to use Machine Learning and Deep Learning Algorithms for projects of varying complexity using Python
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You will make 14 very interesting and enjoyable projects
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Implementation of Image Classification using Deep Learning
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Implementing Time Series Forecasting using Python and Keras Tensorflow
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Implementation of Clustering, Recursive and Sorting Algorithms using Python
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You will learn how to perform sentiment analysis using Machine Learning
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Transfer Learning Implementation using InceptionResNetV2
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Implementing Artificial Neural Networks using Python
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You will practice on the popular Kaggle database used for artificial intelligence training
Who is this course for?
- This course is for anyone interested in Machine Learning, Deep Learning and Artificial Neural Networks.
- Anyone who wants to learn AI skills with practical Python projects
- Software Engineers, Recruiters and Data Scientists who want to move up their career ladder
- Students and professionals who want to develop training capabilities with real-life examples
- Python programmers interested in data science.
Specialization in Artificial Intelligence Projects in Python
Contents 9/2022
Requirements
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A computer with standard instructions (Any operating system – Windows, Mac, Linux are all OK.)
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Basic programming language Python is preferred but not required if you know another programming language.
Pictures
Sample Clip
Installation Guide
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file size
3.18GB