December 2019 marked the beginning of a new era when the Corona-virus was first detected and confirmed as a pandemic. The disease brought about unexpected changes in our lives. With every change that comes in, a new behavior kicks in. Since the start of the pandemic, we have had numerous innovations and inventions. With each innovation, we tend to solve a problem. With a pandemic that limits our social norms such as handshaking and gatherings technology becomes the next stop to evade the limitations.
Covid is here, and it is up to us to use what we have to keep it under control. Is the pandemic a trigger to the start of a new industrial revolution? …
Every new technology ushers a new era. When you combine several technologies together we get more than an era we have a Revolution.
Hello everyone. Today we take a look at the Industrial Revolution Timeline. Starting from the First revolution to the current times as we experience the Fourth industrial revolution.
The industrial revolution is the transition to new manufacturing processes. It involves a change in an economy marked by the general introduction of power-driven machinery or by an important change in the prevailing types and methods of use of such machines.
The major drive of a revolution is emerging technology. Emerging technology; technology whose development, practical applications, or both are still largely unrealized. Technology is the practical application of knowledge. …
“The more we think about how to harness the technology revolution, the more we will examine ourselves and the underlying social models that these technologies embody and enable, and the more we will have an opportunity to shape the revolution in a manner that improves the state of the world.”
― Klaus Schwab
What do you think the future looks like? well, I have an idea Automation becomes part of our life, Advanced health care systems, Quantum computing, just to mention.
What should we expect in the future? Technology is a powerful tool and with it comes changes to the way we know life and society. To be able to answer this question we need to go back in time and look at the revolutions brought by technology. …
“I think you can have a ridiculously enormous and complex data set, but if you have the right tools and methodology, then it’s not a problem.” — Aaron Koblin,
Today we take a look at the characteristics of data and the need to have a clean dataset when working on any project.
Did you know that data is never clean? Data is messy, to understand data a you need to clean it. Clean data is equal to a good and useful ML model. An ML model is dependent on data.
Data Scientists are required to sort out the data to eliminate the errors in untidy data. This process will determine the results you gain from the data. …
Hello, guys today we take a look at computer vision and its applications. Computer vision is an emerging field and it brings numerous applications to our daily life. Looking at this technology and by the end of the article, you will be in a position to explain the need for computer vision.
Computer vision dates back to the 1960s it was designed to mimic the human visual system. This was to enable a computer system to see and describe what it has seen. When Larry Roberts (the father of Computer vision) described the possibilities of extracting 3D geometrical information from a 2D perspective views of blocks. …
What is Machine Learning?
Machine Learning(ML) is a type of Artificial-Intelligence that can extract patterns out of raw data by using algorithms or methods. Machine learning aims at making sense out of data in a similar manner that a human being does. Can a computer learn on their own and perform or make decisions without necessarily being programmed? This is not science fiction but Machine Learning.
Today we take a look at the pertinence of machine learning in our day to day life. We all know that we are in the era of Machine Learning and artificial intelligence. As time goes by we see more and more machine intelligence coming into our world. What does this machine have that makes them an entry to our lives? …
“Learning takes time, and the same goes for a computer. There are no shortcuts nor magic formulas: learning a language is difficult and even automatic processes require time and labor.” Marco Varone
What does it mean to be data-driven or data-dependent? To get one into perspective we take an example of all living things. A simple case is a plant that is enclosed in a box that has a hole in it. In this case, the plant bends and adapts to get to where the light comes from hence we conclude that the plant needs light for optimal growth.
Similarly, Data-driven or Data-dependent means that for a technology to be viable and useful Data is needed. Let us give meaning to the term data-driven. Techopedia defines Data-driven as a process or activity that is spurred on by data, as opposed to being driven by mere intuition or personal experience. The decisions are made with reference to hard empirical evidence and not by speculation or gut feeling. …
Hello everyone! Today I want to write about the Sci-kit-learn Library, it is commonly known as (Sklearn).
It is a useful and robust library for machine learning in Python. It provides a selection of tools for machine learning and statistical modeling by featuring various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, and k-means.
Sci-kit learn is build on top of the following libraries.
Did you know that having the ability to think critically, evaluate, and solve complex problems is what makes a human being the most intelligent and advanced species on earth? This ability has led to research and investment in trying to understand how the human brain works. This curiosity is the major drive to making a machine that learns without being necessarily programmed.
Today we look at Machine learning(ML). We shall try to understand what ML is, What revolves between machine learning, and the need to understand ML concepts
“Things get done only if the data we gather can inform and inspire those in a position to make a difference.” — Mike Schmoker
Everything has a start and an end, between the initialization and the termination, a process has to take place. Data science is a process that involves numerous steps that enable us to make sense of the data we have. These several steps can turn raw, unorganized, meaningless data into an organized meaningful dataset that tells a story. The number one fact in data is that data is never clean.
Every process always aims at a particular goal. In this case, the data science process always aims at achieving a given goal. For this to take place the following steps have to be followed. …