Starting from the hypothesis testing, the blog is explaining the concept and major differences between z-test and t-test.

*Are the observed changes in mean statistically significant?*

This is perhaps a major consideration while making a critical hypothesis that gives a perfect analysis for a condition. Such analysis are the excellent candidates for hypothesis testing, or in other words, significance testing.

For testing the hypotheses various test statistics are performed, such as t-test and z-test, and that will be the main course of discussion during the blog.

**We will cover main topics as;**

- Hypothesis Testing
- What is Z-test?
- What is T-test?
- …

An official is appointed who investigates complaints, made by citizens, independently, impartially and confidentially, learn everything about an ombudsman and its 7 types

The word “Ombudsman” evolved from the Swedish ombudsman, signifying* “the legal representative”.* Initially, the Swedish legislature made the designation of the ombudsperson in early 1800, with the translation of ombudsperson as *“the official investigator of citizen complaints”. This person was acknowledged as “the person of legal capabilities and superior virtue.”*

*The Ombudsman is independent, unbiased and gives cost-free services. He/she investigates complaints when problems have been commanded inappropriately or unfairly, or making citizens undergo unfair consequences, some…*

Let us learn the theory of conditional probability in context with definition, examples and properties through this blog.

Being a classical concept in probability theory, the conditional probability is one of the prominent approaches of measuring the probability of occurrence of an event, provided that another event has occurred.

*Introduction

*What is the conditional probability?

- Conditional probability of independent events
- Conditional probability of mutually exclusive events
- Chain rule or multiplication rule
- The law of total probability

*Properties of conditional probability

*Examples of conditional probability, and

*Ending notes

First, let’s catch the quick introduction to the concept of probability.

*Can we…*

Data Lakes vs. Data Warehouses, when and how to use, catch the difference between the two most famous options for storing big data.

Talking about buzzwords today regarding data management, and *listing here is Data Lakes, and Data Warehouse, what are they, why and where to deploy them*. So, in this blog, we will *unpack their definition, key differences, and what we see in the near future.*

“The world is now awash in data and we can see consumers in a lot clearer ways.” — —Max Levchin, PayPal co-founder.

There are several modes to stockpile big data, but the…

Increasing the level of Delhi Pollution is perilous, predicting air pollution levels using machine learning techniques and the role of IoT in blue sky analytics.

*Delhi pollution was mentioned in the news,*

Have you overheard that pollution level in Delhi spreading very quickly, yes, soo contaminated, how are people breathing their,

A curious me looked at Delhi, we are breathing here, really a polluted air, contaminated environment, an inquisitive me echoed in the news if and how I can contribute to controlling Delhi Pollution, hey listen! can’t we use the tardiest technologies in it, can we? Yes, we can!!!

In…

With a broad bandwidth of options for big data, storage and more, discover how Google Cloud Platform(GCP) has become the public cloud that is the prime preference for many organizations’ users.

Cloud computing has become the buzzword as its market crossed billion of users, today it is delivering tremendous benefits and advantages. The huge necessity for scalability and the elevated cost of electricity is the prime acumens behind the cloud evolution.

Initially, Salesforce and Amazon were the essence players in the cloud industry, but soon, Google launched its ** Google Cloud Platform(GCP)**. …

This blog explains an Automatic Machine Learning (AutoML) is an automated end-to-end process of applying ML to real-world applications.

In recent years, Machine Learning has propelled in many aspects, counting model structuring and various methods of leaning. It is plausible today to explore entire machine learning algorithms via fundamental operations as fabricating blocks.

Also, the essence of neural networks have touched the remarkable performance on various tasks and observed a rapid growth in their popularity, it is only achievable because of diverse machine learning research into a vast realm ranging from learning strategies to new neural architectures.

However, the length…

Amazon’s machine learning university is proffering its online course accessible to the public, covering NLP, computer vision and tabular data.

*Amazon’s Machine Learning University has made its online courses available to the public, commencing with Accelerated Natural Language Processing.*

Previously, it was accessible to Amazon’s employees, but now freely-accessible to everyone. Let’s dive deep in course details.

Machine learning, a computational science domain that probes patterns and structures across data and helps out in understanding, decision-making and argumentation without human interaction.

*As they as, “Data is the quintessence for businesses, so machine learning benefits in diagnosing signals amongst the data…*

Computer vision is a relatively developing section of computer science that attempts to obtain as much as possible information from the various sort of images or sequences of images.

Being a subject of growing interest and precise research for decades that is broadly deployed in* scene restoration, object modeling, visualization, navigation, recognition, surveillance, virtual reality, or similar tasks*.

“Real learning, attentive, deep learning, is playful and frustrating and joyful and discouraging and exciting and sociable and private all the time, which is what makes it great.” —Eleanor Duckworth

This article is a quick tutorial on** how to redefine surveillance…**

As Josh Wills once said,

“Data Scientist is a person who is better at statistics than any programmer and better at programming than any statistician.”

*Defined by Wikipedia “statistics is the study of the **collection, analysis, interpretation,** presentation, and organization of data”. *So, the data scientists need to know statistics along with machine learning, and deep learning concepts.

Consider a simple case of data analysis that demands minimally “descriptive statistics” and “probability theory” in order to make better business decisions from data. These prime concepts involve probability distributions, statistical significance, hypothesis testing, and regression.

In this blog, we go through…

The Single-minded determination to win is crucial- Dr. Daisaku Ikeda | LinkedIn: http://linkedin.com/in/neelam-tyagi-32011410b