一定要去看他们在GitHub上提供的实验和代码,尤其是Introduction to TensorFlow(github.com/aamini/intro)。再说一遍,自己动手编写代码非常重要!!! 5. PyCharm入门 时间:3小时(取决于计算机的速度)。费用:免费。帮助级别:10/10(必须使用PyCharm)。 考试在PyCharm(Python开发工具)中
为了方便初学者和开发者进行学习,官方在 deeplearning.ai 和 Udacity 都提供了相关教程。 deeplearning.ai 教程地址:https://www.coursera.org/learn/introduction-tensorflow Udacity 教程地址:https://cn.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187 2.0 正式版有哪些更新 主要特性和改进 Ten...
MIT introduction deep learning lecture 1 - gives a great overview of what's happening behind all of the code we're running. Reading: 1-hour of Chapter 1 of Neural Networks and Deep Learning by Michael Nielson - a great in-depth and hands-on example of the intuition behind neural networks...
TensorFlow: Advanced Techniques from Coursera TensorFlow 2 for Deep Learning Specialization from Coursera Intro to TensorFlow for A.I, M.L, and D.L from Coursera Machine Learning with TensorFlow on GCP from Coursera Intro to TensorFlow for Deep Learning from Udacity Introduction to TensorFlow Lite ...
🎥Introduction to machine learning and time seriesby Markus Loning goes through different time series problems and how to approach them. It focuses on using thesktimelibrary (Scikit-Learn for time series), though the principles are applicable elsewhere. ...
一定要去看他们在GitHub上提供的实验和代码,尤其是Introduction to TensorFlow(https://github.com/aamini/introtodeeplearning/)。再说一遍,自己动手编写代码非常重要!!! 5. PyCharm入门 时间:3小时(取决于计算机的速度)。 费用:免费。 帮助级别:10/...
https://www.coursera.org/specializations/tensorflow-in-practice 课程讨论 欢迎扫码进入微信群讨论 欢迎提issue,如果微信邀请码失效请提issue 课程目录 Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning A New Programming Paradigm ...
machine-learning natural-language-processing certificate deep-learning tensorflow coursera series tensorflow-tutorials convolutional-neural-network introduction deeplearning-ai introduction-to-tensorflow tensorflow-developer-certificate practice-specialization Updated Oct 10, 2020 Jupyter Notebook palas...
import requestsbirthdata_url = 'https://github.com/nfmcclure/tensorflow_cookbook/raw/master/01_Introduction/07_Working_with_Data_Sources/birthweight_data/birthweight.dat'birth_file = requests.get(birthdata_url)birth_data = birth_file.text.split('\r\n')birth_header = birth_data[0].split('...
birthdata_url ='https://github.com/nfmcclure/tensorflow_cookbook/raw/master/01_Introduction/07_Working_with_Data_Sources/birthweight_data/birthweight.dat'birth_file = requests.get(birthdata_url) birth_data = birth_file.text.split('\r\n') ...