Surely, I can help you. Please drop an email to me on
email@example.com and we shall coordinate and connect on this.
Rundeck is runbook automation. Give anyone self-service access to the operations capabilities that previously only your subject matter experts could perform.
Popular use cases include incident management, service requests, business continuity, or just spreading the operational load among your colleagues.
This blog will be on setting up the Rundeck in your modern distributed or centralized environment, to help you monitor virtual machines or execute some task remotely. In the first part of the series, I will be covering the following scenario.
1. Setting up Rundeck on VM
2. Creating a Rundeck Project
3. Creating a New Job
4. Executing A Job on Local VM
This article gives a brief introduction to how you can load test gRPC based applications written in any programming languages like Java or Python using an open-source tool called Locust.io. This article preassumes that you have a good understanding of gRPC service and python as a programming language. Locust doesn’t support gRPC officially but this blog will help you in implementing it when you need to load test your applications based on gRPC.
To learn about gRPC, you can browse through the official documentation. …
Machine learning can be majorly classified into two types.
It can be thought of as a teacher supervising the learning process, Here given a training dataset with some feature value as (x) and target/output (y), algorithms try to learn from it and create a mapping function so that given a new input on x it can predict the approximate value of y. Supervised learning problems can be further grouped into regression and classification.
It can be thought of as given a learning material you need to find out how many different syllabi it can make based on some pattern. Here…
Descriptive statistics help you to understand the data, but before we understand what data is, we should know different data types in descriptive statistical analysis. The below screen helps you to get an overview of it.
A data set is a grouping of information that is related to each other. A data set can be either qualitative or quantitative. A qualitative data set consists of words that can be observed, not measured. A quantitative data set consists of numbers that can be directly measured. …
We will try to evaluate our machine learning models on different error metrics. We need to remember while evaluating models that it should be immune to class imbalance if our data set is a classical example to imbalance data set. We will deal with typical imbalance dataset examples in upcoming blogs.
A list of few popular Evaluation Metrics are followings.
For Classification Problem:
1. Confusion Matrix
2. Precision / Recall
3. F1 Score
4. Area Under the ROC curve (AUC — ROC)
5. Cohen’s Kappa
For Regression Problem:
1. Root Mean Squared Error(RMSE)
2. R-Squared/Adjusted R-Squared
Lets try an understand…
In school we have been taught so many stories about life and living, like the story of an ant when it tries to climb a wall and fails most of the time but finally makes it not because of the last attempt it made but because of its self-belief that it could make it. Maybe it couldn’t consider the attempt made by it as it’s last towards its goal but simply giving it a try as long as it could do. This is what happens with us in real life too when we keep attempting towards our goals and when…
Failure or achievement in one’s life will always be temporary; one can’t be assured that he will always be winner or loser. They are just like some wave pattern where one day you might witness the crest or trough of it. Crest signifies the good time of the wave and trough the other part of it. But both just signify the pattern of the wave which it follows. When studied this nature I discovered be it any, either crest or trough both has rise and fall in themselves and both touches peak value of it. It just that if in…
Hypothesis is a statement about the population that might be true.The beauty of these Hypotheses is that they can be TESTED!
To understand this topic we will take help of data.
Example: We have a hypothesis that ‘the average salary of the Data Scientists in Bay Area and Montreal is different’.
Most of the times we have certain assumptions about population parameters, hypothesis testing is a way to decide whether these assumptions stand true based on the data from sample.
There are two types of statistical hypotheses:
Alternate Hypothesis [H1] — is a hypothesis which researcher tries to prove. It…
Computer Science Engineer with a passion for Machine Learning, AI & Data Visualization. Transforming world with data.