Author Archives: Ankit Das - Page 4
This article is an attempt to check under what condition we can go for a Z -Test or a T-Test. We will further implement these tests in python.
The post Z-Tests vs T-Tests: How To Choose Among Two Important Hypothesis Tests appeared first on Analytics India Magazine.
The vocabulary helps in pre-processing of corpus text which acts as a classification and also a storage location for the processed corpus text. Once a text has been processed, any relevant metadata can be collected and stored.In this article, we will discuss the implementation of vocabulary builder in python for storing processed text data that can be used in future for NLP tasks.
The post How To Create A Vocabulary Builder For NLP Tasks? appeared first on Analytics India Magazine.
The vocabulary helps in pre-processing of corpus text which acts as a classification and also a storage location for the processed corpus text. Once a text has been processed, any relevant metadata can be collected and stored.In this article, we will discuss the implementation of vocabulary builder in python for storing processed text data that can be used in future for NLP tasks.
The post How To Create A Vocabulary Builder For NLP Tasks? appeared first on Analytics India Magazine.
In the real world, the size of datasets is huge which comes as a challenge for every data science programmer. Working on it takes a lot of time, so there is a need for a technique that can increase the algorithm’s speed. Most of us are familiar with the term parallelization that allows for the distribution of work across all available CPU cores. Python offers two built-in libraries for this process, multiprocessing and multithreading.
The post Optimization In Data Science Using Multiprocessing and Multithreading appeared first on Analytics India Magazine.
In recent times, ensemble techniques have become popular among data scientists and enthusiasts. Until now Random Forest and Gradient Boosting algorithms were winning the data science competitions and hackathons, over the period of the last few years XGBoost has been performing better than other algorithms on problems involving structured data. Apart from its performance, XGBoost is also recognized for its speed, accuracy and scale. XGBoost is developed on the framework of Gradient Boosting.
The post Complete Guide To XGBoost With Implementation In R appeared first on Analytics India Magazine.
In real-world, training and model prediction is one phase of the machine learning life-cycle. But it won’t be helpful to anyone other than the developer as no one will understand it. So, we need to create a frontend graphical tool that users can see on their machine. The easiest way of doing it is by deploying the model using Flask.
In this article, we will discuss how to use flask for the development of our web applications. Further, we will deploy the model on google platform environment.
The post Complete Guide To Model Deployment Using Flask in Google Cloud Platform appeared first on Analytics India Magazine.
In this era, Short message service or SMS is considered one of the most powerful means of communication. As the dependence on mobile devices has drastically increased over the period of time it has led to an increased number of attacks in the form of SMS Spam.The main aim of this article is to understand how to build an SMS spam detection model. We will build a binary classification model to detect whether a text message is spam or not.
The post Hands-On Guide To Detecting SMS Spam Using Natural Language Processing appeared first on Analytics India Magazine.
How do you know what machine learning algorithm to choose for your problem? Why don’t we try all the machine learning algorithms or some of the algorithms which we consider will give good accuracy. If we apply each and every algorithm it will take a lot of time. So, it is better to apply a technique to identify the algorithm that can be used.
Choosing the right algorithm is linked up with the problem statement. It can save both money and time. So, it is important to know what type of problem we are dealing with.
The post How To Choose The Best Machine Learning Algorithm For A Particular Problem? appeared first on Analytics India Magazine.
The main aim of this article is to discuss the methods for checking the stationarity in time series data. We will do the experiments on the time series data to check this.
The post How To Check Time-Series Stationarity?A Beginners Guide in Python appeared first on Analytics India Magazine.
This article demonstrates how we can implement a deep learning model with ShuffleNet architecture to classify images of CIFAR-10 dataset. Here, we define a Convolutional Neural Network (CNN) model using Torch to train this model. We will test the model to check the reduction in computational cost and obtain accuracy.
The post Complete Guide To ShuffleNet V1 With Implementation In Multiclass Image Classification appeared first on Analytics India Magazine.