Data Science, Artificial Intelligence and Machine Learning

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Unveiling the World of Data Science, AI, Machine Learning and Deep Learning

Welcome to an instructive journey where we delve into the captivating realms of data science, AI, machine-learning and deep learning. Forked over about a decade in IT, I am your guide in this journey, Sandhya Krishna.

Understanding Data in the Digital Era

In this digital epoch, data is the modern oil fuelling the economy. This treasure trove is characterized into open data with unrestricted access and closed data requiring certain permissions. The mammoth influx of data offers us a challenge. The data we collect may be raw, inconsistent, incomplete, without trends and filled with errors, but after refinement and application of statistical advanced tools, it transforms into valuable insights. These insights further morph into knowledge which is beneficial in resolving issues related to business analytics and technical aspects.

The World of Business Intelligence (BI) and Business Analytics (BA)

BI and BA play pivotal roles in dealing with data. BI helps in the delivery of information timely and accurately, aiding in better decision-making. Business Analytics is a larger spectrum that engages artificial intelligence, statistical tactics, IT and management strategies to generate meaningful insights.

It primarily focuses on four analytical areas:

  • Descriptive Analytics: Records the events.
  • Diagnostic Analytics: Determines why did the event occur.
  • Predictive Analytics: Forecasts future events.
  • Prescriptive Analytics: Guides on future course of action.

With the integration of predictive techniques in BI, the field of Business Analytics emerges.

Artificial Intelligence: The Game Changer

Artificial Intelligence (AI) is often misconstrued as a job killer, but it is fundamentally a job transformer. AI is integrating into our daily work lives, automating tedious work and providing better insights. According to great personalities like Elon Musk, Mark Cuban and Jeffrey Hinton, the sheer understanding and correct application of AI can be a game changer in businesses.

AI emulates human behavior in decision-making, text processing, visual perception, etc. AI has been branched into various capabilities like narrow intelligence (best example being Siri), general intelligence and superintelligence. It functions via reactive machines, limited memory, theory of mind and self-awareness.

What is Machine Learning (ML)?

Machine Learning leverages algorithms to identify patterns in data and generate insights. One can think of AI and ML in terms of Venn diagrams, where ML is the path to achieve AI. ML algorithms can be broadly classified into three categories:

  • Supervised Learning: The model is trained with labeled data.
  • Unsupervised Learning: Here, we don't have labeled data and the model learns to figure out patterns.
  • Reinforcement Learning: This is a mixture of supervised and unsupervised learning and is used when training data is minimal.

A Peek into Deep Learning (DL)

Deep Learning, much like ML, also imitates the neural network of the human brain, but the difference being DL works on unstructured data. DL uses neural networks to learn from unstructured and unlabeled data. It segments the data into input, hidden (or feature) layer and output layer, identifying patterns, and predicting outputs.

In conclusion, these are not just technological advancements; they are powering solutions to complex problems, transforming the way businesses operate, and influencing how data is driven. For any queries, feel free to reach out, and let's continue our voyage in this ocean of knowledge.

Email: [email]

References:

  1. AI & Machine Learning: The Basics. (n.d.). Digital Marketing Institute.
  2. Expert System. (2017, April 3). AI & Machine Learning: The Benefits and Challenges to Business.
  3. SAS. (n.d.). What is Artificial Intelligence?
  4. SAS. (n.d.). What is Machine Learning?
  5. SAS. (n.d.). What is Deep Learning?

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