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Use TensorFlow to take machine learning to the next level. Your new skills will amaze you.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Machine learning
- Resource Type:
- Others
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MOOC
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
- Course related:
- AMA564 Deep Learning
- Subjects:
- Computing
- Keywords:
- Machine learning Neural networks (Computer science) Artificial intelligence
- Resource Type:
- MOOC
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Video
A series of video that cover various computing topics, for example, C++ programming, C# programming, Python, and Java.
- Subjects:
- Computing
- Keywords:
- Computer programming
- Resource Type:
- Video
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Video
This channel walks you through the entire process of learning to code in Python; all the way from basics to advanced machine learning and deep learning. The primary emphasis will be on image processing and other relevant functionality. Why did I create this channel? To help you (students and researchers) gain a new skill and succeed in your respective fields.
You may think coding is hard and that it's not your cup of tea, but Python made it easy to code even advanced algorithms. In addition, coding will make you self sufficient, it will teach you how to think, it improves your collaborative skills and it can take your career to new heights. Therefore, if you want to stay ahead of your peers and relevant in your field, overcome your fears and start coding!
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Video
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Others
We're like Duolingo for learning to code. When learning to code, most people get stuck on the "bridge" between memorizing syntax and understanding the logic that makes it all work. We believe the most effective way to learn a programming language is to break the process into three phases:(1)Memorize syntax; (2) Solve problems; and (3) Make stuff. Most beginners jump from memorizing syntax directly into making stuff (or trying) without fully understanding how syntax is used to solve problems. In other words, they haven't learned how to think like a programmer, yet they're trying to solve problems like a programmer. Edabit was created to bridge this gap, while also making the process fun and addictive.
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- Computer programming
- Resource Type:
- Others
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e-book
This text is designed to introduce and expand upon material related to the C programming language and embedded controllers, and specifically, the Arduino development system and associated Atmel ATmega microcontrollers. It is intended to fit the time constraints of a typical 3 to 4 credit hour course for electrical engineering technology and computer engineering technology programs, although it could also fit the needs of a hardware-oriented course in computer science. As such, the text does not attempt to cover every aspect of the C language, the Arduino system or Atmel AVR microcontrollers. The first section deals with the C language itself. It is assumed that the student is a relative newcomer to the C language but has some experience with another high level language, for example, Python. This means concepts such as conditionals and iteration are already familiar and the student can get up and running fairly quickly. From there, the Arduino development environment is examined. Unlike the myriad Arduino books now available, this text does not simply rely on the Arduino libraries. As convenient as the libraries may be, there are other, sometimes far more efficient, ways of programming the boards. Many of the chapters examine library source code to see “what's under the hood”. This more generic approach means it will be easier for the student to use other processors and development systems instead of being tightly tied to one platform. There is a lab manual for this textbook.
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Others
Discover the most effective way to improve your models.
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Python (Computer program language)
- Resource Type:
- Others
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e-book
The book is based on “First semester in Numerical Analysis with Julia”, written by Giray Ökten. The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index, a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based interactive development environment for Python as well as many other programming languages, was used throughout the book and is recommended to the readers for easy code development, graph visualization and reproducibility.
- Subjects:
- Computing
- Keywords:
- Numerical analysis Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
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Video
This video presents an overview of the Fourier Transform, which is one of the most important transformations in all of mathematical physics and engineering. This series will introduce the analytic theory of the Fourier Transform, along with the Fast Fourier Transform (FFT) algorithm for efficient computations. We will explore lots of applications in image compression, audio analysis, and solving partial differential equations.
- Course related:
- EIE4413 Digital Signal Processing, EIE3331 Communication Fundamentals, and EE3312 Linear Systems
- Subjects:
- Mathematics and Statistics
- Keywords:
- Fourier transformations
- Resource Type:
- Video
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Others
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and games.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Data structures (Computer science) Programming languages (Electronic computers) Computer networks Computer algorithms
- Resource Type:
- Others