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Machine Learning is the art of computing, in which we need first to prepare the data, if not in well-formed condition and then use that accurate data to train the models. The models are built on different algorithms, which the programmers need to write in programming language and our case it is Python. Based on the previous output of the data and algorithmic logic, Machine starts to learn themselves, and the accuracy of the future values are accurate more and more based on the vast amount of data that we have collected.
The RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! When predicting with my model error occurs when the input tensors and the model are on different devices (e.g., one on CPU and the other on GPU). To fix the RuntimeError: Expected all tensors to be … Read more
The RuntimeError: The size of tensor a (4000) must match the size of tensor b (512) at non-singleton dimension 1 error occurs when you exceed the maximum input length limitation, usually 512 tokens. To fix the RuntimeError: The size of tensor a (4000) must match the size of tensor b (512) at non-singleton dimension 1 error, you … Read more
The TypeError: ‘tensorflow.python.framework.ops.EagerTensor’ object is not callable error occurs when you try to call a TensorFlow EagerTensor object as if it were a function or method. If you forget to use the .numpy() method to convert the EagerTensor to a NumPy array before calling it, this TypeError will be raised. See the below code. import tensorflow … Read more
In this tutorial, we will see How To Install Tensorflow on Mac. For this tutorial, you must have installed Python 3 on your mac machine. If not, go to the python.org website and install version 3 of Python. Other than that, you need to have an editor like Visual Studio Code. You can always welcome with PyCharm IDE as … Read more
Machine Learning is about training your model based on current data to predict future values. So we need the proper amounts to train our model. So in real life, we do not always have the correct data to work with. We must prepare and train our model if the data is not processed correctly. So … Read more
