Python广泛应用于机器学习, 人工智能和统计数据分析等课程. 它也被很多大学作为入门语言来教授. 目前是我们代写最多的编程语言.
Deep Learning – COSC2779 – Introduction to Deep Learning Deep Learning – COSC2779 Introduction to Deep Learning Dr. Ruwan Tennakoon July 19, 2021 Lecture 1 (Part 1) Deep Learning – COSC2779 July 19, 2021 1 / 16 Outline 1 Introduction: Teaching Team 2 Course Overview 3 Introduction to Deep Learning 4 Review of Machine Learning […]
Lab Exercises | Week 1 COSC2779 – Deep Learning 1 Introduction In this weeks lab, we will explore deep learning infrastructure that will be used during the course. The main cloud based platforms we will be using are: • Google Colab • (optional) Kaggle Notebooks GPU The following text will provide an introduction on setting
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Digression: Scoring Matrices Lecture 2 The Software Development Process L2 Software Development Process- 2 Objectives of This Lecture • Getting started with Python/Thonny • To know the steps of a software development process • Understand and write simple Python statements • Understand the concept of pseudocode • Elements of a program L2 Software Development Process-
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COSC2779LabExercises_W2_3_solutions-checkpoint ¶ COSC 2779 | Deep Learning ¶ Week 1-2 Lab Exercises: **Introduction to Tensorflow** ¶ introduction¶ This lab is aimed at introducing the fundamentals of TensorFlow 2.0. The Lab is organized into six sub modules: Minimal example: 2D Linear regression. Exercise: Classifying hand written text MNIST. Advanced TensorFlow example: Understanding gradient tape and writing
Digression: Scoring Matrices Lecture 3 Writing code in Python L3 Introduction to Python – 2 Revision: Getting Started with Python Start with single statements >>> 2+3 5 >>> 22/7 3.142857142857143 >>> 3**2 9 >>> print(“Hello world”) Hello world >>> print(“2+3=“, 2+3) 2+3=5 L3 Introduction to Python – 3 Revision: Temperature Converter program “”” convert.py A
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Digression: Scoring Matrices CITS1401 Computational Thinking with Python Lecture 0 Introduction L0 Introduction – 3 My introduction • Unit Coordinator: Dr. Ghulam Mubashar Hassan • Consultation time : 2 – 3 pm Tuesdays • My research areas: Artificial Intelligence, Machine Learning interdisciplinary problems & Engineering Education • Website: www.csse.uwa.edu.au/~00080148/ • Office: CSSE Room: 2.12 or
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Digression: Scoring Matrices Lecture 14 File Processing Part II L14 File Processing Part II – 2 Objectives • To understand the basic text file processing concepts in Python. • To learn how to read and write text files in Python and string formatting. • Take an example to read data from a file, process it
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COSC2779LabExercises_W2_3 ¶ COSC 2779 | Deep Learning ¶ Week 1-2 Lab Exercises: **Introduction to Tensorflow** ¶ introduction¶ This lab is aimed at introducing the fundamentals of TensorFlow 2.0. The Lab is organized into six sub modules: Minimal example: 2D Linear regression. Exercise: Classifying hand written text MNIST. Advanced TensorFlow example: Understanding gradient tape and writing
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Digression: Scoring Matrices Lecture 17 Nested Loops L17 Nested Loops – 2 Objectives • To understand the use of nested loops. • To be able to design and implement solutions to problems involving loop patterns. – Post test loops – Loop and a half • To understand the use of break and continue statements. L17
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extra-visualisation Introduction¶ These exercises are intended to demonstrate some of the visualisation options matplotlib is capable of, and to give you an opportunity to practice visualisations outside of the lab. In these exercises you will: learn how to visualize a set of data using a Python library called matplotlib. find out different forms of visualization,
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