Machine Learning (ML)

Data Visualization using Tableau

In this article, we have explored how Tableau can be used for data visualization by using it on Population dataset.

ResNeXt architecture

In this article, we have explored the ResNeXt model architecture which has been developed by Facebook. We have provided a Python implementation of ResNeXt along with applications of the model.

Machine Learning (ML)

Compare two different Audio in Python

In this article, we have explored how to compare two different audio in Python using librosa library.

data science

Cross entropy method for optimization

In this article, we will understand the cross entropy method that is widely used as an optimization technique in machine learning.

data science

Simulated Annealing

In this article, we will understand what simulated annealing is and get to know its uses in Probability and Data Science.

data science

Monte Carlo Sampling Techniques

In this article, we will explore the various Monte Carlo sampling techniques used in Probability and Data Science.

data science

Data Visualization

In this article, we will understand more about data visualization, different charts used and explore some Data Visualization tools.

Machine Learning (ML)

SGEMM

In this article, we have covered SGEMM (Single Precision General Matrix Multiplication) which is a standard library function for Matrix Multiplication.

Machine Learning (ML)

Questions on Convolution operation in ML

In this article, we have presented several Interview Questions (MCQs) with detailed answers on Convolution in Machine Learning models.

Machine Learning (ML)

YOLOR model architecture

In this article, we have covered YOLOR model architecture in depth and compared it with other YOLO variants like YOLOv4.

data science

Data Warehousing using SSIS

In this article, we will learn how SQL Server Integration Services (SSIS) is used for Data Warehousing in Data Science.

data science

Data Warehousing

In this article, we will understand the concept of Data Warehousing in Data Science and get an idea of some tools used for data warehousing.

TensorFlow

tf.reshape(): Reshape tensors in TensorFlow

In this article, we have explored the idea of Reshaping tensors in TensorFlow with tf.reshape() and which models like GoogleNet use it.

Machine Learning (ML)

Similarity Search on Big Vector Data

In this article, we have explored Similarity Search on Big Vector Data along with Nearest Neighbor Search (NNS) or Approximate Nearest Neighbor Search (ANNS).

data science

Using Python for Data Analysis

In this article, we will learn how Python is used for Data Analysis and introduced Python libraries that are frequently used in Data Science such as Numpy, Pandas, Matplotlib, Seaborn and others.

data science

Data Analysis tools

In this article, we will get the basic idea of what is data analysis and look into some tools that are used for data analysis.

TensorFlow

Max Pool and Avg Pool in TensorFlow

In this article, we have explored Max Pool and Avg Pool in TensorFlow in depth with Python code using the MaxPool and AvgPool ops in TensorFlow.

data science

R squared and Adjusted R squared

In this article, we have explored the idea of R squared and Adjusted R squared which are frequently used in Regression Analysis to analyze data.

Machine Learning (ML)

A/B Testing

In this article, we will learn more about the famous A/B testing which is an important topic in Data Science to find best performing experiments.

TensorFlow

Conv2D operation in TensorFlow

In this article, we have explained Conv2D operation in TensorFlow along with API definition and Python implementation.

TensorFlow

Depthwise Convolution op in TensorFlow (tf.nn.depthwise_conv2d)

This article will discuss about the Depthwise Convolution operation and how it is implemented using the TensorFlow framework (tf.nn.depthwise_conv2d).

Machine Learning (ML)

KL Divergence

In this article , one will learn about basic idea behind Kullback-Leibler Divergence (KL Divergence), how and where it is used.

Machine Learning (ML)

Supervised, Unsupervised and Semi-Supervised Learning

In this article, we will learn more about the differences between Supervised, Unsupervised and Semi-Supervised Learning.

TensorFlow

Graphs in TensorFlow (tf.Graph)

In this article, we have explored the idea of Graphs in TensorFlow in depth along with details of how to convert function (tf.function) to graph (tf.Graph).

Machine Learning (ML)

OpenPose Systems

In this article, we have explored the idea of OpenPose Systems in depth which is used for Pose Detection application using Machine Learning.