Experienced Ph.D. with a demonstrated history of working in the higher education industry. Skilled in Data Science, AI, Deep Learning, Big Data, & Mathematics.

The Data Science Project Cycle series consists of 5 separate articles, and this part is the fourth article in the series. In this part, we will talk about “Modelling and Model Evaluation”.

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https://area.autodesk.com/blogs/the-maya-blog/rigging-and-grooming-a-3d-cartoon-character-in-maya/

Note: I usually will use some abbreviated words below:

  • Data Science — DS
  • Artificial Intelligence — AI
  • Machine Learning — ML
  • Big Data — BD
  • Deep Learning — DL
  • Statistical Learning — SL

Let’s continue…

Modelling and Model Evaluation

We have data free of all kinds of pollution, mess and anomalies, and it’s time to prophesy!

The question is this: I’m going to build a predictive model, I have many algorithms. But the coolest is the X algorithm used in a competition I’ve seen in the kaggle. …


The Data Science Project Cycle series consists of 5 separate articles, and this part is the third article in the series. In this part, we will talk about “Feature Engineering”.

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https://www.lynda.com/Python-tutorials/Applied-Machine-Learning-Feature-Engineering/2824235-2.html

Note: I usually will use some abbreviated words below:

  • Data Science — DS
  • Artificial Intelligence — AI
  • Machine Learning — ML
  • Big Data — BD
  • Deep Learning — DL
  • Statistical Learning — SL

Let’s continue…

1. Feature Engineering

Since we are talking about a ML-oriented project development process, we can gather the titles of tidy process, exploratory data analysis and data manipulation under this heading. Each of these titles has a special importance. …


The Data Science Project Cycle series consists of 5 separate articles, and this part is the second article in the series. In this part, we will talk about “Literature & Best Practice, and Data Understanding”.

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https://libguides.sph.uth.tmc.edu/systematic-review-guidance

Note: I usually will use some abbreviated words below:

  • Data Science — DS
  • Artificial Intelligence — AI
  • Machine Learning — ML
  • Big Data — BD
  • Deep Learning — DL
  • Statistical Learning — SL

Let’s continue…

Literature and Best Practice Search

Since there is no need to re-discover the world, to investigate what kind of solutions the world has found in related issues and to investigate the suitability of the approaches that are known to be successful at the point of application, if any, for the relevant project. …


It is not possible to make flow loops that cover every Data Science project. However, the question of how should a Data Science project cycle be for projects with Machine Learning output will be tried to be answered in these article series. This series consists of 5 separate articles and is the first article in this series. In this part, we will talk about “Business Understanding”.

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https://bigdataanalyticsnews.com/10-essential-skills-you-need-to-be-a-data-scientist/

Note: I usually will use some abbreviated words below:

  • Data Science — DS
  • Artificial Intelligence — AI
  • Machine Learning — ML
  • Big Data — BD
  • Deep Learning — DL
  • Statistical Learning — SL

Let’s…


Do you say I want to become a Data Scientist but I don’t know how to start? Then I am offering you a roadmap. For this, I will experience what you have to do and try to rank it based on what I see.

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https://www.analyticsvidhya.com/blog/2020/01/learning-path-data-scientist-machine-learning-2020/

Hey Data Scientist Candidate!

Take the first step by updating your LinkedIn profile now: Data Scientist Candidate, Data Science Enthusiast or Data Science Researcher. Write even if you don’t feel ready, no one is born a data scientist out of the womb. …


This series of articles consists of 4 main chapters and this article is “Who Is A Data Scientist, What Is It, What Does It Do?” is the last part of the series.

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Photo by https://sapienceconsultancyblog.com/2019/08/07/what-is-takes-to-be-a-data-scientist/

At the end of our article series, let’s look for answers to the basic questions that may come to mind for those who want to become a Data Scientist.

Questions

1.Is It Necessary to Have All of These Features to Become a Data Scientist?
Make sure No. For example; Data science projects can also be taken in cases where cloud technologies, big data technologies and even open source software are not needed. A Data Science Project can also be taken with SPSS and SAS. A data science project can also be done by modeling on a small amount of data set. The important point here is that the Data Scientist should extract meaningful information from the data using the above TOOLS. …


This series of articles consists of 4 main chapters and this article is “Who Is A Data Scientist, What Is It, What Does It Do?” is the third part of the series.

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Photo by https://morioh.com/p/7307bd81da1e

The photo above is a kind of depiction of what the Data scientist did, expertly showing that he was in meditation mode. Every application or feature that you do / will do as you love your job will give you a kind of pleasure and you will enjoy that job.

Now, Briefly What Was Data Science?

In all kinds of assets that can be defined as data; Data science is the entire process of information-oriented work that defines the current situation, makes information-oriented discoveries, categorizes, classifies and makes predictions about the future through the current situation. Statistics, machine learning, programming, big data and open source software are used extensively in data science processes. However, socially; “Data Science” deserves the current attention, as it should include skills such as research, inquiry, linking between problems and technical solutions, interpretation and presentation of findings. …


This series of articles consists of 4 main chapters and this article is “Who Is A Data Scientist, What Is It, What Does It Do?” is the second part of the series.

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Photo by https://ople.ai/ai-blog/what-does-it-take-to-become-a-data-scientist/

As you have read this article, you are aware that a large amount of data is generated at any time and that this data must be made meaningful quickly. A new data-oriented understanding is emerging for human beings, who have become data-driven at every point from our entertainment channels to our defense systems. In short:

We are all data now. We expect to be made meaningful with our whole life. …


This series of articles consists of 4 main chapters and this article is “Who Is A Data Scientist, What Is It, What Does It Do?” is the first(fun part) of the series.

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Photo by https://gibsonjones.com/2019/04/15/hiring-a-data-scientist/

Note: As you will read below, I tried to make similarities between them. I know that someone with an academic background should have gone technically based on data rather than saying this is the result directly, but the purpose of this article is to completely warm up and prepare for the next article of this series.

Let’s start…

I tried to write the subject of the Data Scientist, which is not known to be of much value and what is known by other countries except America, Canada and to a lesser extent the UK, in a way that I hope will attract attention in a different way. …


This article series consists of 4 main parts and this article is “What is data science?” is the last in the series.

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Photo by https://www.corpnce.com/relationship-ai-ml-dl-ds/

Note: I usually will use some abbreviated words below:

  • Data Science — DS
  • Artificial Intelligence — AI
  • Machine Learning — ML
  • Big Data — BD
  • Deep Learning — DL

Lets talk about DS, AI and ML?:

AI has never been among the things I have written so far.

So where is AI at work?

In response, we can consider using DS as a lever to explain the relationship between ML and AI. If you do a research online, you will find that people are a bit confused about the relationship between these three disciplines. While some include ML in DS, others tend to perceive it as a part of AI. We are not going to come out with a classification that will end all discussions. …

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