Author: Dr. Pranay Jha
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ML Concepts – Loss Function in ANN
The Loss Function is one of the important components of Neural Networks. Loss is nothing but a prediction error of Neural Net. And the method to calculate the loss is called Loss Function.In simple words, the Loss is used to calculate the gradients. And gradients are used to update the weights of the Neural Net.…
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ML Concepts – Optimization Algorithm for Training Neural Network Model
Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning rate in order to reduce the losses.• Gradient Descent• Stochastic Gradient Descent• Mini-Batch Gradient Descent• Momentum• Nesterov Accelerated Gradient• Adagrad• AdaDelta• Adam (Adaptive Moment Estimation)
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ML Concepts – Linear Regression vs Logistic Regression
Classification Regression Analysis Linear vs Logistic Regression More about Logistic Regression Steps in Preparing Model using Logistic Regression
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ML Concepts – Understanding the Dataset
What is Dataset? Usually dataset refers to the data that you have, it is combined of both dependent as well as independent variables. In ML lingo, dataset is the pair (X, y) where X refers to set of independent variables and y is the target. X is also called the feature set. Moreover, using variables/features…
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ML Concepts – Classification vs Regression
Classification Regression – Classification is the task of predicting a discrete class label.– In a classification problem data is labelled into one of two or more classes.– A classification problem with two classes is called binary, more than two classes is called a multi-class classification.– Classifying an email as spam or non-spam is an example…
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ML Concepts – Encoding Categorical Data
There are two types of encoding the Categorical Data: One Hot Encoding Label Encoding or Target Encoding Example: One Hot Encoding – 100, 101, 010 Label Encoding – Normal = 0, Malicious = 1
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ML Concepts – ROC vs AUC
ROC (Receiver Operating Characteristic) AUC (Area Under Curve) – ROC Curve represents relationship between Recall and Specificity. – It is a performance measurement for the binary classification. – It is probability curvet plotted with TPR against the FPR. – AUC Curve represent the degree of measure of separability. – Higher the AUC, the better the…
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ML Concepts – What is Feature Scaling?
Feature Scaling Feature scaling is technique that will get mean and standard deviation of your feature in order to scale your feature. If we apply the feature scaling before the splitting the dataset, then it takes the mean and standard deviation of all the values including training set. It will cause the information leakage. We…
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ML Concepts – Feature Selection – Filter Method vs Wrapper Method
Feature selection is a critical step that affects the ML model performance directly. Reducing the number of features has two main benefits in developing machine learning models. First, extracting a subset from the whole feature list helps to build a more accurate model by removing the noise caused by unnecessary features. Second, model training time…
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ML Concepts – Some common questions need to be answered when you start Data Processing
When you are doing any research for any purpose or performing any task related to Data Processing, you need to understand few questions before start this. I am mentioning few here, you can also add more questions in comment box based on your experience. What is Structure and Unstructured Dataset? What is Primary and Secondary…
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Protected: Most common questions that you need to find before starting a Research
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List of Publications – Journal Articles, Books, Chapters
Title of Publication Name of Journal / Conference Authors ISSN No/ VOL No, Issue No How can your IT Infrastructure Withstand the Pressure of Digitalization? International Journal of Research in Electronics and Computer Engineering Dr. Pranay Jha*, Dr Ashok Sharma http://nebula.wsimg.com/b205966c404e7bf650de85b2f6c3a86e?AccessKeyId=DFB1BA3CED7E7997D5B1&disposition=0&alloworigin=1 IJRECE Vol.7 Issue 1(January-March 2019)ISSN:2393-9028(Print)|ISSN:2348-2281(Online) Behavior Analysis and Crime Prediction using Big Data and…
Architect’s Toolkit
PJ’s Tools
VMware Cloud Foundation
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- VCF 9 Planning & Preparation Workbook
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Nutanix
AI & Cloud-Native Platform
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Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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