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Understanding AI

  • Difficulty Level : Medium
  • Last Updated : 22 Sep, 2021

It’s a long day. I have to drive home all by myself. What if someone takes me home? Have you ever thought how great it would be if your car drives you home itself? Yes, it is possible. Self-Driving cars take you anywhere by themselves. It’s not new at all. Well! In 1939, Norman Bel Geddes proposed the concept of self-driving vehicles at GM’s exhibit. In 1958, General Motors came up with the one. Not just this. Researchers at MRC London Institute of Medical Sciences made it possible to know when a patient’s heart is about to fail. A chatbot, virtual assistant clears all your basic queries in no time. Many more applications like Personalized online shopping, weather prediction, food serving robots in restaurants, smartwatches reduced human effort and time. All these we have today are because of Artificial Intelligence.

What is AI?

Artificial Intelligence is the machinery form of a human. AI technology enables a machine to think and act like a human. An AI model learns from experience as a human does. It learns from the hidden patterns in the data. With AI, humans can complete the work 90% faster. In recent times, we could see AI applications in almost every field like sales, fashion, education, social media, agriculture, healthcare, security, etc. 

So, Do you think this technology is new? 

If your answer is yes, you are wrong. AI was first introduced in 1943 by Warren McCulloch and Walter pits. They proposed a model of artificial neurons. Herbert Simon and Allen Newell created the first AI program in December 1955, proving 38 of the first 52 theorems in Whitehead and Russell’s Principia Mathematica. 

But why is AI recently got into the spotlight? 

We could see AI everywhere recently. The main reason behind this is enormous data. Compared to earlier, we have tones of data now. AI needs data to learn and predict the future. I always wondered why data is enormous now but not then? If you think carefully, the primary source of information is us. We, humans, generate tones of data every single second. Live example, while I have created text data here, you are reading my article and creating a memory. So, the increase in population opened the gate of data productivity. So, the increase in population opened the gate of data productivity that helped AI technology establish in every field. 

How does AI Works?

  1. Business problem understanding: A clear understanding of the problem statement is necessary to get the desired outcome. ask the client as many questions as possible. Gather relevant information. Focus on what changes the client expecting in the business from the conclusion of this project. Analyze risks and challenges.  
  2. Data collection & Data Wrangling: Collect relevant data. The amount of data defines the model performance. So more data, the accurate the model is. Data Wrangling is preprocessing the data before feeding the model. Clean the noise data, identify missing values, outliers, skewness, etc. The perfect the data is, the better the outcome. 
  3. Exploratory & Statistical analysis of Data: Explore the data derive insights and relations between the features. Eliminate the features that are less correlated or not correlated with the target feature. Perform statistical analysis to under the data better. This step is crucial to know the nature and hidden patterns of the data that helps to choose the model.
  4. Model building: The crucial step of the entire process is model building. Split the dataset into train and test data to train the model and check its performance on test data. Build the appropriate model according to the problem statement.
  5. Model evaluation: Validation is always necessary to obtain an accurate outcome. Evaluate the model’s performance using accuracy score, R2 score, classification report, etc. Improve the performance with respective methodologies if necessary.
  6. Deploy and maintain: Once the model gains the confidence of predicting future events, deploy it for end-users availability. Run maintenance checks regularly and keep the model updated. 

Conclusion: 

We could see wounders in the future with AI. AI could change the world completely. It enables humans to achieve the impossible. Thirty years from now, we could see robots living with us. Known fact, there is always good and evil as well. AI could help humans do wonder and also destroy if not used in the way it should be. 

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