Essays about: "Tensorflow."

Showing result 1 - 5 of 122 essays containing the word Tensorflow..

  1. 1. ML implementation for analyzing and estimating product prices

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Abel Getachew Kenea; Gabriel Fagerslett; [2024]
    Keywords : Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

    Abstract : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. READ MORE

  2. 2. Book retrieval system : Developing a service for efficient library book retrievalusing particle swarm optimization

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Adam Woods; [2024]
    Keywords : Particle swarm optimization; indoor positioning system; machine learning; Wi-Fi; RSSI; RTT; artificial neural network; ADAM optimizer; Keras; TensorFlow;

    Abstract : Traditional methods for locating books and resources in libraries often entail browsing catalogsor manual searching that are time-consuming and inefficient. This thesis investigates thepotential of automated digital services to streamline this process, by utilizing Wi-Fi signal datafor precise indoor localization. READ MORE

  3. 3. Modeling Stoppage Time as a Convolution of Negative Binomials

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Råvan Talani; [2023]
    Keywords : Machine learning; negative binomial; convolution; stoppage time; injury time; extra time; football;

    Abstract : This thesis develops and evaluates a probabilistic model that estimates the stoppage time in football. Stoppage time represents the additional minutes of play given after the original matchtime is over. It is crucial in determining the course of events during the remainder of a match, thereby affecting the odds of live sports betting. READ MORE

  4. 4. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    University essay from KTH/Mekatronik och inbyggda styrsystem

    Author : Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Keywords : Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Abstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE

  5. 5. The impact of pruning Convolutional Neural Networks when classifying skin cancer

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Gustaf Larsson; Marcus Odin; [2023]
    Keywords : ;

    Abstract : Over the past few years, there have been multiple reports showcasing how Convolutional Neural Networks (CNNs) can be used to classify if skin lesions are cancerous or non-cancerous. However, a limitation of CNNs is the large number of parameters resulting in high computation times. READ MORE