Introduction Creating precise machine learning models capable of identifying and locating multiple objects in a single image remains a core challenge in computer vision. However, with recent advancements in deep learning, object detection applications are easier to develop than ever before. The TensorFlow Object Detection API is an open-source framework built on top of TensorFlow … Read more
What is Scikit-learn? Scikit-learn is an open-source Python library that includes various unsupervised and supervised learning techniques. It is built on technologies and libraries such as Matplotlib, Pandas, and NumPy, which help simplify coding tasks. Features of Scikit-learn include: Classification (including K-Nearest Neighbors) Preprocessing (including Min-Max normalization) Clustering (including K-Means++ and K-Means) Regression (including Logistic … Read more
Remember when TensorFlow 2.0 was first released? A lot of developers were complaining: The official documentation was hard to find, bugs were not fixed and updated in a timely manner, and so on. Despite being online for so long, many developers still refuse to upgrade from 1.x or migrate from other frameworks. In fact, TensorFlow … Read more
Source: Authorized by AI Technology Camp (ID: rgznai100) This article is approximately 3000 words long and is recommended to be read in 7 minutes. This article will introduce you to a comprehensive manual detailing TensorFlow 2.0. [ Guide ]After the official release of TensorFlow 2.0, it immediately received widespread attention and praise from the academic … Read more
https://iamarookie.blog.csdn.net/article/details/117755839 Basic Operations in TensorFlow2 – Part 3 Merge and Split tf.concat tf.concat helps us perform concatenation operations. Format: tf.concat( values, axis, name='concat' ) Parameters: values: a tensor or tensor list – axis: the dimension to operate on – name: the name of the operation, defaults to “concat” Example: part_1 = tf.zeros([5, 3]) print(part_1) part_2 … Read more
Deep learning frameworks have played a crucial role in the rapid development in recent years, among which PyTorch and TensorFlow are the two most popular frameworks. They each have unique features and advantages, but there are also some similarities. This article will delve into PyTorch and TensorFlow, providing a detailed introduction from principles, code implementation, … Read more
This article was first published on WeChat public account: “The Beauty of Algorithms and Programming”, welcome to follow for more timely updates on this series of articles. Problem Description Here is an example of recognizing the mnist handwritten dataset. This dataset is a classic dataset in machine learning, consisting of 60k training samples and 10k … Read more
Original content from Machinery Industry Education, please share to your circle of friends. Unauthorized reproduction by other public accounts is prohibited. TensorFlow Deep Learning Tutorial Click on the cover View details “TensorFlow Deep Learning Tutorial” (ISBN: 978-7-111-70365-5), Chief Editors: Ping Zhenyu and Kuang Liang,This book comes with micro-course videos, electronic courseware, source code, course standards, … Read more
Author: Arjun Sarkar Translator: Chen Zhiyan Proofreader: Ouyang Jin This article is about 1900 words, and is recommended for an 8minute read. This article will teach you how to write custom loss functions using wrapper functions and OOP in Python. Tags: TensorFlow 2, Loss Function Figure 1: Gradient Descent Algorithm (Source: Public Domain, https://commons.wikimedia.org/w/index.php?curid=521422) Neural … Read more
LearnExcelTechnology, Follow WeChat Official Account: excelperfect Introduction: Here I record the issues encountered while installing TensorFlow and their solutions, so that I can refer back to them later and for the reference of friends facing similar problems. Recently, I have been focusing on studying Deep Learning Illustrated. When I reached Chapter 8, I tried to … Read more