tensorflow Using TensorFlow addons on Mac with M1 These days I am building an image classifier using an unbalanced dataset. So instead of Accuracy, I am more interested in viewing Precision and Recall, or the F1 score. The F1 score metric is implemented by https://www.tensorflow.org/addons/api_docs/python/
tensorflow Using the Keras Tuner Recently I read about the Keras Tuner. A hyperparameter tuner in machine learning is a piece of software that will train random combinations of models in order to find the best architecture. See https://www.tensorflow.org/tutorials/keras/keras_tuner. The idea is
m1 Installing scikit-learn, panda, scipy, numpy on a Mac with M1 Before installing scikit-learn, you should install its dependencies. Installing PandasPandas installs fine with pip install pandas. However, when I tried to import it in my Jupyter Lab notebook, it crashed with this error: ValueError Traceback (most recent call last) <ipython-input-2-b6c7f9fc9652> in <
machine learning Survey of Keras's image related generators In François Chollet's Deep learning with Python, he teaches how to build image classification models using ImageDataGenerators. Let's look into how these are made and how to use them. tf.keras.preprocessing.image.ImageDataGeneratorGenerate batches of tensor image data with real-time data augmentation.TensorFlowBasic
machine learning Displaying a confusion matrix in TensorFlow I recently started dabbling in TensorFlow by training an image classifier. My classifier has a few classes, and instead of blindly judging its accuracy, I decided to look at the confusion matrix to see which classes it recognized well and which it didn't. Multiclass
machine learning Fixing `RuntimeError: tf.gradients is not supported when eager execution is enabled. Use tf.GradientTape instead.` I was following a code sample to visualize convnet filters from Chollet's book. And because of TensorFlow 2's API change, the original code breaks telling us to use tf.Gradient. Note that this is a work in progress. I have not managed to fix
machine learning Installing TensorFlow 2.4 and JupyterLab on Mac with M1 (outdated) This post is now outdated since Apple released TensorFlow 2.5 optimized for Macs, which is twice as fast as TensorFlow 2.4 was on my M1. See how to install it at http://blog.wafrat.com/installing-tensorflow-2-5-and-jupyter-lab/. A few weeks ago (see Getting
machine learning Using Kaggle datasets in Colab Here's how I got Kaggle datasets into Colab. The book I'm following referred to the Dogs vs Cats dataset. After creating an account, I went to the dataset page. Dogs vs. Cats | KaggleCreate an algorithm to distinguish dogs from catsKaggleOne way would be to
machine learning Getting started with ML: Colab or self-hosted Jupyter? The basic trade off is well-known. If you use an online VM like Google's Colab or Amazon's EC2 instances, you don't need hardware, but the cost of running the VMs will get expensive later. If you self-host, you need to buy some dedicated hardware,