# Tag Archives: python

## SVM Classifier using Sklearn: Code Examples

In this post, you will learn about how to train an SVM Classifier using Scikit Learn or SKLearn implementation with the help of code examples/samples. An SVM classifier, or support vector machine classifier, is a type of machine learning algorithm that can be used to analyze and classify data. A support vector machine is a supervised machine learning algorithm that can be used for both classification and regression tasks. The Support vector machine classifier works by finding the hyperplane that maximizes the margin between the two classes. The Support vector machine algorithm is also known as a max-margin classifier. Support vector machine is a powerful tool for machine learning and has been widely used …

## Stochastic Gradient Descent Python Example

In this post, you will learn the concepts of Stochastic Gradient Descent (SGD) using a Python example. Stochastic gradient descent is an optimization algorithm that is used to optimize the cost function while training machine learning models. The most popular algorithm such as gradient descent takes a long time to converge for large datasets. This is where the variant of gradient descent such as stochastic gradient descent comes into the picture. In order to demonstrate Stochastic gradient descent concepts, the Perceptron machine learning algorithm is used. Recall that Perceptron is also called a single-layer neural network. Before getting into details, let’s quickly understand the concepts of Perceptron and the underlying learning …

## Dummy Variables in Regression Models: Python, R

In linear regression, dummy variables are used to represent the categorical variables in the model. There are a few different ways that dummy variables can be created, and we will explore a few of them in this blog post. We will also take a look at some examples to help illustrate how dummy variables work. We will also understand concepts related to the dummy variable trap. By the end of this post, you should have a better understanding of how to use dummy variables in linear regression models. As a data scientist, it is important to understand how to use linear regression and dummy variables. What are dummy variables in …

## Correlation Concepts, Matrix & Heatmap using Seaborn

In this blog post, we’ll be discussing correlation concepts, matrix & heatmap using Seaborn. For those of you who aren’t familiar with Seaborn, it’s a library for data visualization in Python. So if you’re looking to up your data visualization game, stay tuned! We’ll start with the basics of correlation and move on to discuss how to create matrices and heatmaps with Seaborn. Let’s get started! Introduction to Correlation Correlation is a statistical measure that expresses the strength of the relationship between two variables. The two main types of correlation are positive and negative. Positive correlation occurs when two variables move in the same direction; as one increases, so do …

## Python – Matplotlib Pyplot Plot Example

Matplotlib is a matlab-like plotting library for python. It can create both 2D and 3D plots, with the help of matplotlib pyplot. Matplotlib can be used in interactive environments such as IPython notebook, Matlab, octave, qt-console and wxpython terminal. Matplotlib has a modular architecture with each layer having its own dependencies which makes matplotlib very versatile and allows users to use only those modules they need for their applications. matplotlib provides many hooks that allow developers to customize matplotlib features as they need. Matplotlib architecture has a clear separation between user interface and drawing code which makes it easy to customize or create new interfaces for matplotlib. In this blog …

## Elbow Method vs Silhouette Score – Which is Better?

In K-means clustering, elbow method and silhouette analysis or score techniques are used to find the number of clusters in a dataset. The elbow method is used to find the “elbow” point, where adding additional data samples does not change cluster membership much. Silhouette score determines whether there are large gaps between each sample and all other samples within the same cluster or across different clusters. In this post, you will learn about these two different methods to use for finding optimal number of clusters in K-means clustering. Selecting optimal number of clusters is key to applying clustering algorithm to the dataset. As a data scientist, knowing these two techniques to find …

## Hello World – Altair Python Install in Jupyter Notebook

This blog post will walk you through the steps needed to install Altair graphical libraries in Jupyter Notebook. For data scientists, Altair visualization library can prove to very useful. In this blog, we’ll look at how to download and install Altair, as well as some examples of using Altair capabilities for data visualization. What is Altair? Altair is a free statistical visualization library that can be used with python (2 or 3). It provides high-quality interactive graphics via an integrated plotting function ́plot() that produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. Altair is also easy to learn, with intuitive commands like ‘plot’, ‘hist’ …

## Free Python & R Training from Spoken Tutorial Initiative

Many people today are interested in learning Python and R. Are you starting on data science and machine learning and looking to get trained with python and R skills? These two programming languages are very popular because they allow for the analysis of data sets that is not possible with other tools. The training offered at Spoken Tutorial Initiative will introduce you to Python and R, while also providing helpful tips on how to use them effectively. Spoken Tutorials Initiative by IIT Bombay is an initiative of NME (National mission on Education) through Govt. of India, ICT, MoE to promote IT literacy on free and open source software (FOSS) by …

## 14 Python Automl Frameworks Data Scientists Can Use

In this post, you will learn about Automated Machine Learning (AutoML) frameworks for Python that can use to train machine learning models. For data scientists, especially beginners, who are unfamiliar with Automl, it is a tool designed to make the process of generating machine learning models in an automated manner, user-friendly, and less time-consuming. The goal of Automl is not just about making it easier for machine learning (ML) developers but also democratizing access to model development. What is AutoML? AutoML refers to automating some or all steps of building machine learning models, including selection and configuration of training data, tuning the performance metric(s), selecting/constructing features, training multiple models, evaluating …

## Python Scraper for GoogleNews, Twitter, Reddit & Arxiv

In this post, you will get the Python code for scraping latest and greatest news about any topics from Google News, Twitter, Reddit and Arxiv. This could prove to be very useful for data scientist, machine learning enthusiats to keep track of latest and greatest happening in the field of artificial intelligence. If you are doing some research work, these pieces of code would prove to be very handy to quickly access the information. The code in this post has been worked out in Google Colab notebook. First and foremost, import the necessary Python libraries such as the following for GoogleNews, Twitter and Arxiv. Python Code for mining GoogleNews Here …

## Reddit Scraper Code using Python & Reddit API

In this post, you will get Python code sample using which you can search Reddit for specific subreddit posts including hot posts. Reddit API is used in the Python code. This code will be helpful if you quickly want to scrape Reddit for popular posts in the field of machine learning (subreddit – r/machinelearning), data science (subreddit – r/datascience), deep learning (subreddit – r/deeplearning) etc. There will be two steps to be followed to scrape Reddit for popular posts in any specific subreddits. Python code for authentication and authorization Python code for retrieving the popular posts Check the Reddit API documentation page to learn about Reddit APIs. Python code for …

## Mining Twitter Data – Python Code Example

In this post, you will learn about how to get started with mining Twitter data. This will be very helpful if you would like to build machine learning models based on NLP techniques. The Python source code used in this post is worked out using Jupyter notebook. The following are key aspects of getting started with Python Twitter APIs. Set up Twitter dev app and Python Twitter package Establish connection with Twitter Twitter API example – location-based trends, user timeline, etc Search twitter by hashtags Setup Twitter Dev App & Python Twitter Package In this section, you will learn about the following two key aspects before you get started with …

## Python Scraper Code to Search Arxiv Latest Papers

In this post, you will learn about Python source code related to search Arxiv for relevant and latest machine learning and data science research papers. If you are looking for a faster way to research on Arxiv papers without really going to the Arxiv website, you may want to get this piece of code in your kitty. You can further automate the Arxiv search to get notified based on some logic. Without further ado, let’s get started. Step 1: Install Python Arxiv Library As a first step, install the Python Arxiv library using the code such as below in your Jupyter notebook or Google colab instance: Step 2: Execute the …

## Google News Search Python API Example

In this post, you will learn about how to use GoogleNews search Python library to get or retrieve or scrape news from Google News for last N number of days. This would be very helpful for someone wanting to track new work / projects in relation to machine learning, data science, deep learning or any field including sports, politics etc. Without further ado, lets jump in right away. You can log into Google colab and practise the code. Step 1: First and foremost, lets install GoogleNews python library. Step 2: Instantiate GoogleNews object. One can pass the language and period to instantiate the object. The parameter, period, represents the news …

## Python – How to Create Dictionary using Pandas Series

In this post, you will learn about one of the important Pandas fundamental data structure namely Series and how it can be used as a dictionary. It will be useful for beginner data scientist to understand the concept of Pandas Series object. A dictionary is a structure that maps arbitrary keys to a set of arbitrary values. Pandas Series is a one-dimensional array of indexed data. It can be created using a list or an array. Pandas Series can be thought of as a special case of Python dictionary. It is a structure which maps typed keys to a set of typed values. Here are the three different ways in …

## Free Online Books – Machine Learning with Python

This post lists down free online books for machine learning with Python. These books covers topiccs related to machine learning, deep learning, and NLP. This post will be updated from time to time as I discover more books. Here are the titles of these books: Python data science handbook Building machine learning systems with Python Deep learning with Python Natural language processing with Python Think Bayes Scikit-learn tutorial – statistical learning for scientific data processing Python Data Science Handbook Covers topics such as some of the following: Introduction to Numpy Data manipulation with Pandas Visualization with Matplotlib Machine learning topics (Linear regression, SVM, random forest, principal component analysis, K-means clustering, Gaussian …

I found it very helpful. However the differences are not too understandable for me