Implementing Skip-Gram Model with TensorFlow

Implementing Skip-Gram Model with TensorFlow

Author丨Tian Yu Su Zhihu Column丨Machine Learning Link丨https://zhuanlan.zhihu.com/p/27296712 Introduction The second practical code is updated. The previous column introduced the Skip-Gram model in Word2Vec. If you have read it, you can directly start implementing your own Word2Vec model using TensorFlow. This article will use TensorFlow to complete the Skip-Gram model. If you are not familiar with … Read more

Using TensorFlow’s High-Level Estimator Interface (1)

Using TensorFlow's High-Level Estimator Interface (1)

In section 4.4 of the book “Practical Machine Learning Projects with TensorFlow”, the author used skflow. When skflow first came out, it was quite popular, but the interface changed very frequently, leading to a decline in its usage, which also resulted in the code from section 4.4 no longer running. However, in the recently released … Read more

Training and Inference of Safety Helmet Detection Model Using TensorFlow and OpenCV4

Training and Inference of Safety Helmet Detection Model Using TensorFlow and OpenCV4

Click on the above“Beginner Learning Vision” to choose to add “Star” or “Top“ Important content delivered in real-time Development Environment Software Version Information: Windows 10 64-bit TensorFlow 1.15 TensorFlow Object Detection API 1.x Python 3.6.5 VS2015 VC++ CUDA 10.0 Hardware: CPU i7 GPU 1050ti To install the TensorFlow Object Detection API framework, see here: The … Read more

Advanced Practical Training of TensorFlow Based on Python

Advanced Practical Training of TensorFlow Based on Python

Deep learning is a general term for the process of machine learning using multi-layer neural networks. Multi-layer neural networks are models that utilize various mathematical methods and their combinations. In recent years, people have been able to effectively leverage neural networks primarily due to the reality of obtaining sufficient amounts of data and the rapid … Read more

Object Detection Tutorial in TensorFlow: Real-Time Detection

Object Detection Tutorial in TensorFlow: Real-Time Detection

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

Scikit-learn vs TensorFlow: Detailed Comparison

Scikit-learn vs TensorFlow: Detailed Comparison

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

Social Distance Detector Using TensorFlow, Python, and OpenCV

Social Distance Detector Using TensorFlow, Python, and OpenCV

Click on the “Beginner’s Visual Learning” above to select “Star” or “Pin“ Important content delivered promptly 0. Introduction During the pandemic, we searched for TensorFlow pre-trained models on GitHub and found a repository containing 25 object detection pre-trained models with their performance and speed metrics. Utilizing one of these models to build a social distance … Read more

A Comprehensive Guide to TensorFlow 2.0

A Comprehensive Guide to TensorFlow 2.0

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

Learn Basic Operations in TensorFlow2 in One Hour

Learn Basic Operations in TensorFlow2 in One Hour

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

Creating Custom Loss Functions Using TensorFlow 2

Creating Custom Loss Functions Using TensorFlow 2

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