Machine/Deep Learning Engineer at UpWork Freelancer
Real User
2020-11-24T00:24:37Z
Nov 24, 2020
On a scale from one to ten, I would give Caffe a rating of seven. If you're going to use this solution, then you have to learn C++. You need to understand how C++ works so that you'll have a better understanding of how the memory is handled and the resources are handled in C++. After that, you have to start learning Caffe step-by-step. Caffe is a new concept, especially the Blob. Caffe is based on Blob so you need to understand what that is and how it's implemented because, with Caffe, you have to make a transformation to fit that. You need to understand all of this before you start. After that, you have to look at open-source solutions and their code and understand what they are doing and why they are doing it. In order to implement your own solution or to be comfortable using Caffe, you need to be able to read the code, the documentation, and everything before you begin. Someone with no background in Caffe, for example, someone who migrates from TensorFlow or PyTorch, that person will not understand anything because they're completely different. If you want to implement a deep learning model in TensorFlow, it can be done in roughly 10 lines, but with Caffe, it's going to be a completely new project. For these reasons, you need to understand C++ and the concept of Caffe in general. Every day, a ton of papers and articles are published. They are not using Caffe, they are using either TensorFlow or PyTorch. To be honest, I recommend that people start with TensorFlow and PyTorch because I see them as the future; there is something great you can do with them — especially since they support mobile device implementation. If you are working with Caffe, you have to convert your model from Caffe to TensorFlow or PyTorch in order for it to be suitable for mobile applications.
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On a scale from one to ten, I would give Caffe a rating of seven. If you're going to use this solution, then you have to learn C++. You need to understand how C++ works so that you'll have a better understanding of how the memory is handled and the resources are handled in C++. After that, you have to start learning Caffe step-by-step. Caffe is a new concept, especially the Blob. Caffe is based on Blob so you need to understand what that is and how it's implemented because, with Caffe, you have to make a transformation to fit that. You need to understand all of this before you start. After that, you have to look at open-source solutions and their code and understand what they are doing and why they are doing it. In order to implement your own solution or to be comfortable using Caffe, you need to be able to read the code, the documentation, and everything before you begin. Someone with no background in Caffe, for example, someone who migrates from TensorFlow or PyTorch, that person will not understand anything because they're completely different. If you want to implement a deep learning model in TensorFlow, it can be done in roughly 10 lines, but with Caffe, it's going to be a completely new project. For these reasons, you need to understand C++ and the concept of Caffe in general. Every day, a ton of papers and articles are published. They are not using Caffe, they are using either TensorFlow or PyTorch. To be honest, I recommend that people start with TensorFlow and PyTorch because I see them as the future; there is something great you can do with them — especially since they support mobile device implementation. If you are working with Caffe, you have to convert your model from Caffe to TensorFlow or PyTorch in order for it to be suitable for mobile applications.