Here is the list of top 6 paid skills in Information Technology that you should know about.
TensorFlow is an open-source, python-friendly library used for high-performance numerical computation that makes machine learning easier and faster. It replaced “DistBelief,” its closed-source predecessor.
TensorFlow has a flexible architecture which enables an easy deployment of numerical computation across several platforms – TPUs, GPUs, CPUs; from desktops to collections of servers to edge and mobile devices.
It was initially created by engineers and researchers from the Google Brain team for both research and production. It comes with a strong support for deep learning and machine learning for dataflow programming across varieties of tasks.
When it comes to the application of TensorFlow, it is being used by social media companies for photo tagging; image analysis for microscopy; retail stores use it for object detection during checkout; space exploration, automotive, aviation, and healthcare also use it for image and object recognition.Upah Tensorflow Developers
An Azure function app (httptrigger) has to be developed to calculate images with a given model for object detection (tensorflow 2). Requirements concerning environment - Python 3.7.4 has to be used - tensorflow 2.4.1 has to be used - use Linux for Azure function app - You have to use your own Azure environment (no access can be given to my Auzere environment) On my local machine, everything is working fine on my Windows PC. The aim is that I can deploy and run such an Azure function. Source code has to be delivered and maybe help has to be given in setting up the function app. (Actually I deployed many function apps already.) Description of files ==================== Program files: - main python file which is called to run this sample (python .) - doing the real job, load mode...
Main Task - Image Reconstruction 1. Custom image Dataset must be loaded from the local drive. As of now you can load your own dataset. 2. Image Augmentation have to be included Important: There should not be any restriction on the dimensions of the image. It will work with all the image dimensions Step 1: 3. The various types of Autoencoder techniques and GAN must compared with and without hyper parameter tuning, Ensembling methods with various performance metrics. 4. There is an option to mention and control the types of noises with the range 5. The reconstructed results will be checked with the bunch of images or else the single image with similarity score with the input image.
I already have a model that is built using TensorFlow Decision Forests. I have to convert some of the preprocessing steps from pandas to tensorflow. And model building steps. Bid only if you have experience in tensorflow and is available to do it right now.
There is a code written in TensorFlow 1 for developing a deep learning model. I want to convert the code to TensorFlow 2. The new code should: 1. Train the model as fast as the original code (This is the crucial condition about this project) 2. Generate exactly the same quality of results as the original code (with the same dataset that is used for the original code) 3. Be like it is genuinely written in TensorFlow 2 and not only TensorFlow 2 compatible. This is the original code: At the end of the project I will assess the speed of the new code, the performance of the model training process and output of the code. Thanks!
I have started some code for tensor flow and need someone with experience to make some changes so it can run properly. Includes testing the model and then more to be built. Quick job initially.