Article Content :

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Introduction :

Within the increased development of cloud computing services, migration to the public cloud is continuously increasing amongst many industries due to its flexibility and the large wide range of automated services it offers. Amazon Web Services (AWS) provides a broad platform of managed services to help in building, securing, scaling and maintaining data architectures; a company has not to care about server’s maintenance and failures. …

Why data science is important nowadays ?

In order to efficiently use their data, companies are moving from traditional data analytics tools that provide descriptive analytics to visualize “what happening” to predictive and perspective analytics with data science tools.
Predictive analytics help in identifying impacting factor of a target event and answer “why it happens” and finally perspective analytics would use statistical modeling to know “what will happen in the future”.
I wrote this story to help professionals (software developers, accounts, …), data science enthusiasts and other persons intending to build a career reconversion toward data science.

This article would clarify key steps to build a simple predictive model and translate data into business recommendations.
Data science is used in strategic marketing, supply chain management, risk analysis, client churn, cost reduction, diffaiture, etc, predict future sales and future depenses.
Firstly, let’s answer a frequently asked question : what is difference between data engineer & data scientist.

Story Content :

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Deep Learning Enthusiasts may encounter some ambiguity in dealing with many notions overlapping in his mind without understating their concrete use case and separate multiple Reinforcement Learning problems.

This article is designed to alleviate that ambiguity of Reinforcement Learning and gives a complete overview of it without introducing a lot of mathematical details.

It ‘s as well a guideline to understand the intuitively behind RL and helps in formalizing a real world problem into a Reinforcement Learning Model.

I. Reinforcement Learning Success:

Reinforcement learning is a ML concept that learns an agent to automatically select the optimal decision given a situation by improving over time through trial and error in order to achieve a maximum long term reward. …


narjes ka

Cloud & Data Engineer | Data Scientist

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