python

Python Profiling – Memory Profiling (Part 3, Final)

Table of Contents memory_profiler PySpy DISassembling Final Recommendations memory_profiler Similar to line_profiler, memory_profiler provides detailed memory usage measurements, with the aim of efficiently reducing memory consumption and optimizing memory usage to improve application performance.. ⚠️ Before starting using this tool, it is important to mention the impact on the execution...

Continue reading...

TensorFlow High-Level Libraries: TF Estimator

TensorFlow has several high-level libraries allowing us to reduce time modeling all with core code. TF Estimator makes it simple to create and train models for training, evaluating, predicting and exporting. TF Estimator provides 4 main functions on any kind of estimator: estimator.fit() estimator.evaluate() estimator.predict() estimator.export() All predefined estimators are...

Continue reading...

Loss Functions (Part 1)

Implementing Loss Functions is very important to machine learning algorithms because we can measure the error from the predicted outputs to the target values. Algorithms get optimized by evaluating outcomes depending on a specified loss function, and TensorFlow works in this way as well. We can think on Loss Functions...

Continue reading...