Tensorflow How can I make a classifier from a CSV file using TensorFlow?
You can start with this tutorial, and try it first without changing anything; I strongly suggest this unless you are already familiar with Tensorflow so that you gain some familiarity with it.
Now you can modify the input layer of this network to match the dimensions of the HuMoments. Next, you can give a numeric label to each type of aphid that you want to recognize, and adjust the size of the output layer to match them.
You can now read the CSV file using python, and remove any text like "HuMoments". If your file has names of aphids, remove them and replace them with numerical class labels. Replace the training data of the code in the above link, with these data.
Now you can train the network according to the description under the title "Train the Model".
One more note. Unless it is essential to use Tensorflow to match your project requirements, I suggest using Keras. Keras is a higher level library that is much easier to learn than Tensorflow, and you have more sample code online.
I need to create a classifier to identify some aphids.
My project has two parts, one with a computer vision (OpenCV), which I already conclude. The second part is with Machine Learning using TensorFlow. But I have no idea how to do it.
I have these data below that have been removed starting from the use of OpenCV, are HuMoments (I believe that is the path I must follow), each line is the HuMoments of an aphid (insect), I have 500 more data lines that I passed to one CSV file.
How can I make a classifier from a CSV file using TensorFlow?

HuMoments (in CSV file):
  0.27356047,0.04652453,0.00084231,7.79486673,-1.4484489,-1.4727380,-1.3752532
  0.27455502,0.04913969,3.91102408,1.35705980,3.08570234,2.71530819,-5.0277362
  0.20708829,0.01563241,3.20141907,9.45211423,1.53559373,1.08038279,-5.8776765
  0.23454372,0.02820523,5.91665789,6.96682467,1.02919203,7.58756583,-9.7028848