计算机视觉课程 Computer Vision Course

用Python，Tensorflow 2.0，OpenCV，FastAI学习深度学习&计算机视觉。对象检测& GAN和更多！

你会学到什么
在深度学习和计算机视觉中使用最新的工具和技术
学习如何使用最新的Tensorflow 2.0
如何使用GPU和TPU应用迁移学习、集成学习
如何工作并赢得卡格尔比赛
学习使用FastAI
如何使用生成性对抗网络
如何使用权重和偏差来记录实验
学习使用探测器2进行物体探测
从头开始制作机器学习Web应用程序
了解如何将OpenCV用于计算机视觉
如何制作真实世界的应用程序并部署到云中
学习技术，如对象检测、分类和生成
学习如何使用Heroku部署ML模型
致力于Kaggle竞赛和Kaggle内核
使用Matplotlib和Plotly等流行的库探索和可视化数据集。
学习如何使用熊猫、Sklearn、Numpy等图书馆
使用Tensorflow创建高级数据管道以训练深度学习模型
为深度学习和计算机视觉设置环境和项目

MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz
语言：英语 |大小解压后:6.20 GB |时长:16小时43分

要求
基本的Python编程知识
一台可以上网的电脑
本课程中使用的所有工具都是免费的
描述
这个全新的现代深度学习&计算机视觉课程将教会你学习计算机视觉基础所需的一切。

深度学习和计算机视觉是目前人工智能发展最快的领域之一，谷歌、苹果、

脸书、亚马逊在这一领域投入巨大。深度学习和计算机视觉工作每天都在增加&提供了世界上一些薪酬最高的工作。

如果我们想让机器思考，我们需要教它们看。——费李非，斯坦福人工智能实验室和斯坦福视觉实验室主任

计算机视觉让我们能够观察世界，处理数字图像和视频，提取有用的信息来完成分类、物体检测等特定任务。Python是深度学习和计算机视觉中最流行的编程语言之一。

本课程中使用的所有工具、技巧和技术-

学习计算机视觉和深度学习基础知识

设置Anaconda，安装库和Jupyter笔记本

学习OpenCV和Numpy的基础知识——阅读图像、色彩空间、绘图和回调

高级OpenCV -图像预处理、几何变换、透视变换和仿射变换、图像混合和金字塔、图像梯度和阈值、Canny边缘检测器和轮廓

在OpenCV中处理视频——使用网络摄像头、哈尔级联和对象检测、车道检测

深度学习&神经网络如何工作？-人工神经网络、卷积神经网络和迁移学习

图像分类-植物叶片分类

研究最近的Kaggle竞赛

使用Google Colab & Kaggle内核

使用最新的Tensorflow 2.0 & Keras

使用Keras数据生成器和数据论证

使用迁移学习和集成学习

使用最先进的深度学习模型

使用GPU和TPU进行模型训练

超参数调谐

使用权重和偏差记录深度学习实验

保存和加载模型

创建重量与偏差报告并展示项目！

目标检测-麦穗检测

又在卡格尔比赛上工作了！

使用脸书探测器2进行目标探测

从头开始创建COCO数据集

训练更快的RCNN模型和自定义权重和偏差回调

使用Retinanet

保存和加载检测器2型号

生成性对抗网络——创造虚假的树叶图像

了解生成性对抗网络是如何工作的

使用FastAI

创建和训练生成性对抗网络

使用GAN制作假图像

制作ML Web应用程序

Streamlit入门

使用Streamlit从头开始创建ML Web应用程序

制作React Web应用程序

部署ML应用程序

了解如何使用云服务来部署模型和应用程序

使用Heroku

了解如何在GitHub上开源项目

如何展示你的项目给老板和员工留下深刻印象并被录用！

好多加分讲座！

这是包含在包裹里的东西

所有的课程代码都可以免费下载

110多场高清视频讲座(50多场即将推出！)

课程问答中的免费支持

所有视频都有英文字幕

本课程适合您，如果..

…你想学习深度学习和计算机视觉中使用的最新工具和技术

…你想获得更多的经验来赢得游戏比赛

…你想从计算机视觉开始，成为一名计算机视觉工程师

..您对学习图像分类、对象检测、生成式对抗网络、制作和部署机器学习应用程序感兴趣

这门课程是给谁的
你想成为一名计算机视觉工程师并被录用
任何想学习计算机视觉中使用的最新工具和技术的人
你已经是一名程序员了，学习计算机视觉能扩展你的技能吗
谁想学习计算机视觉中使用的新工具和技术
你想获得更多赢得游戏比赛的经验

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.20 GB | Duration: 16h 43m

Learn Deep Learning & Computer Vision with Python, Tensorflow 2.0, OpenCV, FastAI. Object Detection & GAN and much more!

What you’ll learn
Using Latest Tools & Techniques in Deep Learning & Computer Vision
Learning how to used the latest Tensorflow 2.0
How to apply Transfer Learning, Ensemble Learning, using GPUs & TPUs
How to work & win Kaggle Competitions
Learning to use FastAI
How to use Generative Adversarial Networks
How to use Weights & Biases for recording Experiments
Learning to use Detectron2 for Object Detection
Making Machine Learning Web Application from Scratch
Learn how to use OpenCV for Computer Vision
How to make Real World Applications & Deploy into Cloud
Learning Techniques like Object Detection, Classification & Generation
Learning how to use Heroku for deploying ML models
Working on Kaggle Competitions & Kaggle Kernels
Exploring & Visualizing Datasets using popular libraries like Matplotlib & Plotly.
Learinng how to use libraries like Pandas, Sklearn, Numpy
Creating Advance Data Pipelines using Tensorflow for training Deep Learning Models
Setting up Environment & Project for Deep Learning & Computer Vision

Requirements
Basic Python programming knowledge
A Computer with Internet Connection
All tools used in this course are free to use
Description
This Brand New and Modern Deep Learning & Computer Vision Course will teach you everything you will need to know to learn the fundamentals of computer vision.

Deep Learning & Computer Vision is currently one of the most increasing fields of Artificial Intelligence and Companies like Google, Apple,

Facebook, Amazon are highly investing in this field. Deep Learning & Computer Vision jobs are increasing day by day & provide some of the highest paying jobs all over the world.

If We Want Machines to Think, We Need to Teach Them to See.-Fei Fei Li, Director of Stanford AI Lab and Stanford Vision Lab

Computer Vision allows us to see the world & process digital images & videos to extract useful information to do a certain task from classification, object detection, and much more. Python is one of the most popular used programming language in Deep Learning and Computer Vision.

All the tools, techniques & technologies used in this course –

Learning Computer Vision & Deep Learning Fundamentals

Setting up Anaconda, Installing Libraries & Jupyter Notebook

Learning fundamentals of OpenCV & Numpy – Reading images, Colorspaces, Drawing & Callbacks

Advanced OpenCV – Image Preprocessing, Geometrical transformations, Perspective transformations & affine transformations, image blending & pyramids, image gradients & thresholding, Canny Edge Detector and contours

Working with videos in OpenCV – Using webcam, Haar Cascades & Object Detection, Lane Detection

Deep Learning & How Neural Network Works? – Artificial neural networks, Convolution Neural Networks & Transfer Learning

Image Classification – Plant leaf Classification

Working on very recent Kaggle Competitions

Using Google Colab & Kaggle Kernels

Using the latest Tensorflow 2.0 & Keras

Using Keras Data Generators & Data Argumentation

Using Transfer Learning & Ensemble learning

Using State of The Art Deep Learning Models

Using GPU & TPU for Model Training

Hyperparameter Tuning

Using Weights & Biases for recording Deep Learning experimentations

Saving & Loading Models

Creating a Weights & Biases Report & Showcasing the Project!

Object Detection – Wheat heads Detection

Working on Kaggle Competitions, again!

Using Facebook’s Detectron2 for Object Detection

Creating COCO Dataset from scratch

Training Faster RCNN Model and Custom Weights & Biases callback

Using Retinanet

Saving & Loading Detectron2 models

Generative Adversarial Networks – Creating Fake Leaf Images

Learning How Generative Adversarial Networks works

Using FastAI

Creating & Training Generative Adversarial Networks

Making Fake Images using GAN

Making ML Web Application

Getting started with Streamlit

Creating an ML Web Application from scratch using Streamlit

making a React Web Application

Deploying ML Applications

Learning how to use Cloud Services to Deploy Models & Applications

Using Heroku

Learning how to Open Source Projects on GitHub

How to showcase your projects to impress boss & employees & Get Hired!

A lot of bonus lectures!

This is what included in the package

All lecture codes are available for downloadable for free

110+ HD video lectures ( over 50 more to come very soon! )

Free support in course Q/A

All videos with English captions available

This course is for you if..

… you want to learn the Latest Tools & Techniques used in Deep Learning & Computer Vision

… you want to get more experience to Win Kaggle Competitions

… you want to get started with Computer Vision to become a Computer Vision Engineer

.. you are interested in learning Image Classification, Object Detection, Generative Adversarial Networks, Making & Deploying Machine Learning Applications

Who this course is for
You want to become a Computer Vision Engineer & Get Hired
Anyone who want to learn latest tools & techniques used in Computer Vision
You are already a Programmer and what to extend your skills by learning Computer Vision
Who want to learn new Tools & Techniques used in Computer Vision
You want to get more experience for winning Kaggle Competitions
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