Object Detection for Images and Videos with TensorFlow 2.0
Object detection is one of the areas in Deep Learning where much progress has been made. Using a variety of...
Tag: tensorflow
Using SELU with TensorFlow 2.0 and Keras
Neural networks thrive on nonlinear data only when nonlinear activation functions are used. The Rectified Linear Unit, or RELU, is...
Bidirectional LSTMs with TensorFlow 2.0 and Keras
Long Short-Term Memory networks or LSTMs are Neural Networks that are used in a variety of tasks. Used in Natural...
Build an LSTM Model with TensorFlow 2.0 and Keras
Long Short-Term Memory (LSTM) based neural networks have played an important role in the field of Natural Language Processing. In...
Using Deep Learning for Classifying Mail Digits
Deep Learning, the subset of Machine Learning which employs Deep Neural Networks for generating models, can be used for many...
How to check if your Deep Learning model is underfitting or overfitting?
Training a Deep Learning model means that you have to balance between finding a model that works, i.e. that has...
One-Hot Encoding for Machine Learning with TensorFlow 2.0 and Keras
When you are training a Supervised Machine Learning model, you are effectively feeding forward data through the model, comparing the...
One-Hot Encoding for Machine Learning with Python and Scikit-learn
Machine Learning models work with numbers. That is, they are mathematical models which improve themselves by performing mathematical optimization. It...
Python Feature Scaling with Outliers in your Dataset
When you are training Machine Learning models, data preprocessing is an important activity. It is sometimes even crucial to the...
Creating a Multilabel Neural Network Classifier with Tensorflow 2.0 and Keras
Neural networks can be used for a variety of purposes. One of them is what we call multilabel classification: creating...
