- Simple and comprehensive tutorials for machine learning and data preprocessing
- Built on NumPy, scikit-learn, scikit-image, OpenCV, SciPy, and Tensorflow

& Data Science

Data Processing and knowledge discovery in data for learning models and patterns from data for reasoning.

& Computer Vision

Extracting and processing the image information and leverage that for scene analysis and understanding.

& Voice Analysis

Speech signal processing and feature extraction for speaker recognition and automatic speech recognition.

Using massive amount of data and computational power for accurate and robust reasoning based on data

by **Hadi Kazemi** on **2017-06-20 10:09:19**

In this post, you will learn the concept behind Autoencoders as well how to implement an autoencoder in TensorFlow.

by **Amirsina Torfi** on **2017-06-11 23:43:46**

In this tutorial, the objective to decide whether the input image is digit "0" or digit "1" using Logistic Regression. In we are aimed to implement logistic regression for binary classification.

by **Amirsina Torfi** on **2017-06-04 23:51:27**

In the linear regression, the linear relationships will be modeled by a predictor function which its parameters will be estimated by the data and is called a Linear Model. In this tutorial, we will introduce how to train a linear model using TensorFLow and how to showcase the generated model.

by **Amirsina Torfi** on **2017-05-13 13:40:45**

The defined variables in TensorFlow are just tensors with certain shapes and types. The tensors must be initialized with values to become valid. In this tutorial, we are going to explain how to define and initialize variables.