What are Convolutional Neural Networks and why are they important? Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars. Figure 1: Source [1] In Figure 1 above, a ConvNet is able to recognize scenes and the system is able to suggest relevant captions (“a soccer player is kicking a soccer ball”) while Figure 2 shows an examp ..read more

An Artificial Neural Network (ANN) is a computational model that is inspired by the way biological neural networks in the human brain process information. Artificial Neural Networks have generated a lot of excitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing. In this blog post we will try to develop an understanding of a particular type of Artificial Neural Network called the Multi Layer Perceptron. A Single Neuron The basic unit of computation in a neural network ..read more

This R package contains several tools to perform initial exploratory analysis on any input dataset. It includes custom functions for plotting the data as well as performing different kinds of analyses such as univariate, bivariate and multivariate investigation which is the first step of any predictive modeling pipeline. This package can be used to get a good sense of any dataset before jumping on to building predictive models. You can install the package from GitHub. The functions currently included in the package are mentioned below: numSummary(mydata) function automatically detec ..read more

Here is topic wise list of R tutorials for Data Science, Time Series Analysis, Natural Language Processing and Machine Learning. This list also serves as a reference guide for several common data analysis tasks. You can also find this list on GitHub where it is updated regularly. The R Language Awesome-R Repository on GitHub R Reference Card: Cheatsheet R bloggers: blog aggregator R Resources on GitHub Awesome R resources Data Mining with R Rob J Hyndman’s R Blog Simple R Tricks and Tools (Video) RStudio GitHub Repo Tidying Messy Data in R Video Baseball Research with R 600 websites about R I ..read more

Listed below are codes for some useful operations on Pandas DataFrame: Renaming Columns in Pandas Deleting Columns from pandas DataFrame Adding new Column to existing DataFrame Add one Row in a pandas.DataFrame Changing the order of DataFrame Columns Changing data type of Columns Getting a list of the column headers from a DataFrame Converting list of dictionaries to DataFrame Getting row count of pandas DataFrame Most efficient way to loop through DataFrames Deleting DataFrame row based on column value Dropping a list of rows from Pandas DataFrame ..read more

I created a list of Python tutorials for data science, machine learning and natural language processing. This list also exists on GitHub where it is updated regularly. The Python Language Dive Into Python Learn Python Wiki on Reddit Highest Voted Python Questions Python Basic Concepts Quick Reference to Python The Elements of Python Style What does the yield keyword do in Python? Parsing values from a JSON file in Python Python Quora FAQs time-complexity of various operations – list/dict – in current CPython The Guide to Learning Python for Data Science Scripting in Python Python Scripting Tu ..read more

I have complied a topic-wise curated list of Machine Learning and Deep Learning tutorials, codes, articles and other resources. See the full list on GitHub.   ..read more

k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. I have provided below the R code to get started with k-means clustering in R. The dataset can be downloaded from here. # Topics Covered # # 1. Reading data and Summary Statistics # 2. Determining the Optimal Number of Clusters # 3. Running Clustering Algorithm and Visualisations ############################################################################## #Reading data and Summary Statistics #change the working di ..read more

Logistic regression, or logit regression is a regression model where the dependent variable is categorical. I have provided code below to perform end-to-end logistic regression in R including data preprocessing, training and evaluation. The dataset used can be downloaded from here. # Topics Covered # # 1. Reading data and Summary Statistics # 2. Outlier Detection # 3. Missing Value Treatment # 4. Correlation and VIF # 5. Feature Selection Using IV # 6. Creating Training and validation Sets # 7. Running the Logistic Model on Training Set # 8. Evaluating Performance on Validation ..read more

Listed below are codes for some data frame operations that are good to have at your fingertips: Create an empty data.frame Sort a dataframe by column(s) Merge/Join data frames (inner, outer, left, right) Drop data frame columns by name Remove rows with NAs in data.frame Quickly reading very large tables as dataframes in R Drop factor levels in a subsetted data frame Convert R list to data frame Convert data.frame columns from factors to characters Extracting specific columns from a data frame ..read more