datahacker.rs@gmail.com

Tag: ML

#011 TF How to improve the model performance with Data Augmentation?

Highlights: In this post we will show the benefits of data augmentation techniques as a way to improve performance of a model. This method will be very beneficial when we do not have enough data at our disposal. Tutorial Overview: Training without data augmentation What is data augmentation? Training with data augmentation Visualization 1. Training without data augmentation A familiar question is “why should we use data augmentation?”. So, let’s see the answer. In order…
Read more

Spell – A Streamlined Machine Learning Platform

Meet Spell – data science and machine learning startup that raised 15M$ to bring AI and deep learning to the global workforce. Revenue: unknown Location: New York Founded: 2017. Specialties: Artificial Intelligence, Computer, Machine Learning, Software Spell is an end-to-end data science and machine learning platform that provides the infrastructure for companies and developers to prepare, train, deploy, and manage the full life-cycle of Machine Learning and Deep Learning experiments. Moreover, Spell was developed to…
Read more

Top 10 Machine Learning Videos on Youtube

So you want to understand what machine learning is in order to master the field, well guess what? Out there are numerous lectures and free video tutorials and available on the internet along with a reference guide. We will provide you with our top 10 popular resources available on Youtube. #1 CS50 CS50 is a popular channel that uploads regular and well-structured machine learning lectures along with different talks and lectures from Harvard University. #2…
Read more

#007 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Spirals dataset

Highlights: In this post we will see how we can classify a spirals dataset with a shallow neural network implemented in TensorFlow 2.0. Tutorial Overview: Imports and Dataset preparation Building a Neural Network Visualization 1. Dataset: import and preparation Let’s start by importing libraries that we will need in our code. Last time we were using a function from sklearn to create a dataset. Now we are going to make our dataset from scratch. First,…
Read more

#006 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Moons dataset

In this post we will learn how to make a classification of Moons dataset with a shallow Neural network. The Neural Net we will implemented in TensorFlow 2.0 using Keras API. With the following code we are going to import all libraries that we will need. First, we will generate a random dataset, then we will split it into train and test set. We will also print dimensions of these datasets. With the following code…
Read more