Deep Tech
Reporting, analysis and features from AIM's Deep Tech section.
IDLE vs Pycharm vs Spyder: Choosing The Right IDE For Machine Learning
This article discusses how to choose the right IDE for machine learning and elaborates whether there is any right IDE for it too or not.
Bhavishya Pandit ·
Face Emotion Recognizer In 6 Lines of Code
In this article, I’ll be discussing how to create a face emotion recognizer using ‘FER’ library from python.
Jayita Bhattacharyya ·
Hands-On Guide to Datatable Library For Faster EDA
In this article, I’ll be discussing the implementation of the datatable library with a large dataset.
Jayita Bhattacharyya ·
What is Data Leakage in ML & Why Should You Be Concerned
Shraddha Goled ·
Understanding Cohen's Kappa Score With Hands-On Implementation
In this article, we will learn in detail about what Cohen’s kappa is and how it can be useful in machine learning problems.
Bhoomika Madhukar ·
Thinking Beyond Transformers: Google Introduces Performers
Ram Sagar ·
Do Convolutional Networks Perform Better With Depth?
Ram Sagar ·
What Is Vokenization And Its Significance For NLP Applications
Ram Sagar ·
Pseudo Labelling - A Guide To Semi-Supervised Learning
In this article, I’ll be discussing how to generate pseudo labels using the semi-supervised learning technique. Semi-Supervised Learning(SSL) which is a mixture of both supervised and unsupervised learning.
Jayita Bhattacharyya ·
How To Approach A Machine Learning Problem For Beginners?
In this article, you will learn step-by-step how to answer these questions by yourself whilst solving machine learning problems.
Bhavishya Pandit ·
Hands-On Guide To Spline Regression
In this article, we will discuss spline regression with its implementation in python.
Bhoomika Madhukar ·
Z-Tests vs T-Tests: How To Choose Among Two Important Hypothesis Tests
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.
Ankit Das ·
Complete Guide To XGBoost With Implementation In R
XGBoost is developed on the framework of Gradient Boosting.
Ankit Das ·
How To Create A Vocabulary Builder For NLP Tasks?
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 artic…
Ankit Das ·
Optimization In Data Science Using Multiprocessing and Multithreading
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 fam…
Ankit Das ·
Complete Tutorial On LeNet-5 | Guide To Begin With CNNs
To start with CNNs, LeNet-5 would be the best to learn first as it is a simple and basic model architecture. In this article, I’ll be discussing the architecture of LeNet-5 which is the very first convolutional neural network to be built.
Jayita Bhattacharyya ·
Big Tech Breakup: Google Blamed For Running A Monopoly, Case Filed
Ram Sagar ·
How To Create An Image Dataset and Labelling By Web Scraping?
In this article, I’ll be discussing how to create an image dataset as well as label it using python. For creating an image dataset, we need to acquire images by web scraping or better to say image scraping and then label using Labeling sof…
Jayita Bhattacharyya ·
A Tutorial On Google Teachable Machine For Object Classification Without Coding
This article demonstrates Google Teachable Machine in action, you can train and download a deep learning model of your own.
Bhavishya Pandit ·
This Brain-Inspired AI Self-Drives With Just 19 Neurons
Ambika Choudhury ·