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Explore and Visualize a Dataset with Python
In today’s story, you will learn: how to combine and wrangle the data, how to explore and analyze the data, how to create beautiful graphs to visualize your findings Who is this article for: People who work with data a lot People who have a basic understanding of Python and Pandas Recap of the Situation:… Continue reading Explore and Visualize a Dataset with Python
Data Splitting
Scientists offer encounter extraordinarily large data sets. This happens for a very good reason; more data gives a more thorough understanding of the phenomenon they’re studying. But it also creates a problem; as data sets gets larger they become harder and harder to understand and use. One excellent solution is learning how to automatically split… Continue reading Data Splitting
How to Develop a Face Recognition System Using FaceNet in Keras
Face recognition is a computer vision task of identifying and verifying a person based on a photograph of their face. FaceNet is a face recognition system developed in 2015 by researchers at Google that achieved then state-of-the-art results on a range of face recognition benchmark datasets. The FaceNet system can be used broadly thanks to… Continue reading How to Develop a Face Recognition System Using FaceNet in Keras
Data Analysis with Python
In addition to being the sexiest job of the twenty-first century, Data Science is new electricity as quoted by Andrew Ng. A lot of professionals from various disciplines and domain are looking to make a transition into the field of analytics and use Data Science to solve various problems across multiple channels. Being an inter-disciplinary… Continue reading Data Analysis with Python
Mistakes that Data Scientists Make and How to Avoid Them
Data analytics can transform how businesses operate. With companies having tons of data today, data analytics can help companies deliver valuable products and services to customers. Becoming a <a class="aq ca et eu ev ew" href="http://www.datascienceauthority.com/" style="box-sizing: inherit; color: inherit; text-decoration: none; -webkit-tap-highlight-color: transparent; background-repeat: repeat-x; background-image: url(" data:image svg+xml;utf8, "); background-size: 1px 1px; background-position:… Continue reading Mistakes that Data Scientists Make and How to Avoid Them
Statistics For Data Science ..💓..
Ever wished someone would just tell you what the point of statistics is and what the jargon means in plain English? Let me try to grant that wish for you! I’ll zoom through all the biggest ideas in statistics in 8 minutes! Or just 1 minute, if you stick to the large font bits. What’s… Continue reading Statistics For Data Science ..💓..
About Data Science ..🖤
Behold my pithiest attempt: “Data science is the discipline of making data useful.” Feel free to flee now or stick around of a tour of its three subfields. Statistics Machine learning Data-mining / analytics The term no one really defined If you poke around in the early history of the term data science, you see… Continue reading About Data Science ..🖤
Understanding data
Musings on information, memory, analytics, and distributions Everything our senses perceive is data, though its storage in our cranial wet stuff leaves something to be desired. Writing it down is a bit more reliable, especially when we write it down on a computer. When those notes are well-organized, we call them data... though I’ve seen… Continue reading Understanding data
misinformation in data visualization?
Data visualization methods concern the design of graphical representation to summarize the data in analytical processes. From this first statement, it is important for companies to understand the risk that both disinformation and misinformation could represent. And while disinformation is defined as a “false information deliberately and often covertly spread in order to influence public… Continue reading misinformation in data visualization?
Data science changing the world ……😝
Purpose of Data Science The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. Then, he has the responsibility of making predictions from the data. The… Continue reading Data science changing the world ……😝
