Total 83 Posts

## Kernel Density Estimation in Python Using Scikit-Learn

### Introduction

This article is an introduction to kernel density estimation using Python's machine learning library scikit-learn.

Kernel density estimation (KDE) is a non-parametric method for estimating the probability density function of a given random variable. It is also referred to by its traditional name, the Parzen-Rosenblatt Window method, after its

## Deep Learning in Keras - Building a Deep Learning Model

### Introduction

Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.

In many of these applications, deep learning

## Translating Strings in Python with TextBlob

### Introduction

Text translation is a difficult computer problem that gets better and easier to solve every year. Big companies like Google are actively working on improving their text translation services which enables the rest of us to use them freely.

Apart from their great personal use, these services can be

## Deep Learning in Keras - Data Preprocessing

### Introduction

Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.

In many of these applications, deep learning

## Deep Learning Models in Keras - Exploratory Data Analysis (EDA)

### Introduction

Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.

In many of these applications, deep learning

## What's New in Tensorflow 2.0?

### Introduction

If you are a Machine Learning Engineer, Data Scientist, or a hobbyist developing Machine Learning Models from time to time just for fun, then it is very likely that you are familiar with Tensorflow.

Tensorflow is an open-source and a free framework developed by Google Brain Team written in

## Statistical Hypothesis Analysis in Python with ANOVAs, Chi-Square, and Pearson Correlation

### Introduction

Python is an incredibly versatile language, useful for a wide variety of tasks in a wide range of disciplines. One such discipline is statistical analysis on datasets, and along with SPSS, Python is one of the most common tools for statistics.

Python’s user-friendly and intuitive nature makes running

## Grid Search Optimization Algorithm in Python

### Introduction

In this tutorial, we are going to talk about a very powerful optimization (or automation) algorithm, i.e. the Grid Search Algorithm. It is most commonly used for hyperparameter tuning in machine learning models. We will learn how to implement it using Python, as well as apply it in