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1. HOW TO CREATE YOUR OWN AI www.nidmindia.com

2. Contents • How to create your own Ai • What is Artificial Intelligence • AI Operation and Application • The First Component to Consider When Building the AI Solution Is the Problem Identification • Have the Right Data and Clean It • Create Algorithms • Train the Algorithms • Opt for the Right Platform • Choose a Programming Language • Deploy and Monitor www.nidmindia.com

3. How to create your own ai • It has been obvious that computers may be programmed to carry out exceedingly complicated tasks since the year 1940 when the digital computer was invented. They may play chess or find proofs for mathematical theorems, for instance. In actuality, computers or robots controlled by computers are capable of carrying out human-like jobs. Artificial intelligence can help in this situation. www.nidmindia.com

4. What is Artificial Intelligience Artificial intelligence (AI) refers to a machine's or robot's capacity to do actions normally performed by intelligent beings. A subfield of computer science is AI. AI examples include conversational chatbots, self-driving cars, email spam filters, Siri, Alexa, and similar smart assistants. The Turing Test and the paper "Computing Machinery and Intelligence," by mathematician Alan Turing, explain the core purpose and vision of AI. In his article on artificial intelligence, Turing argued that there isn't a compelling case against computers having the same level of intelligence as humans. www.nidmindia.com

5. AI Operation and Application • Increasingly, building AI systems is becoming less complex and cheaper. • Real-world applications of AI systems are wide-ranging. Below, you can find the most common examples of AI: • Speech Recognition • Also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, is a capability that uses NLP to process human speech into a written format. • Customer Service • Increasingly, more companies are turning to online virtual agents for customer service, thus replacing human agents. www.nidmindia.com

6. Computer Vision • In this case, AI technology allows computers and systems to derive meaningful information from digital images, videos, and other visual inputs. You can see its application in photo tagging on social media. • Discovery of Data Trends • AI algorithms can use consumers’ behavior to discover data trends, allowing companies to build effective cross-selling strategies. As a result, companies can offer relevant add-on recommendations during the checkout process. www.nidmindia.com

7. The First Component to Consider When Building the AI Solution Is the Problem Identification • It's crucial to consider the user's pain point and determine the value proposition (value-prop) that people can obtain from your product before designing a product or feature. A value proposition relates to the benefits you guarantee your clients will receive if they decide to buy your goods. • You can make a product that is more beneficial to users and more useful by figuring out the problem-solving concept. www.nidmindia.com

8. Have the Right Data and Clean It • After framing the issue, you must choose the appropriate data sources. • Organized Data • Data that is well-defined, contains patterns and has searchable parameters is called structured data. Names, addresses, dates of birth, and phone numbers are a few examples. • The Unstructured Data • Unstructured data lacks consistency, uniformity, and patterns. Emails, photos, infographics, and audio are all included. www.nidmindia.com

9. Create Algorithms • You must select the method the computer will use when you instruct it what to do. Computer algorithms can help with that. The mathematical instructions used in algorithms. For the AI model to learn from the dataset, machine learning algorithms for prediction or classification must be developed. • Train the Algorithms The next step in learning how to develop an AI is to train the algorithm using the data that was gathered. It would be better to optimize the algorithm to produce an AI model during very accurate training. To increase the precision of your model, you might require more information. www.nidmindia.com

10. Opt for the Right Platform Private Frameworks You can pick Scikit, Tensorflow, or Pytorch, for instance. These are the ones that are most frequently used for internal model development. The Cloud Frameworks You may train and deploy your models more quickly using a platform for machine learning as a service or in the cloud. To create and distribute your models, you can utilize IDEs, Jupyter Notebooks, and other graphical user interfaces. www.nidmindia.com

11. Choose a Programming Language • There are various programming languages, such as Python, R, Java, and traditional C++. Because they provide a rich set of tools like vast ML libraries, the latter two programming languages are more well-known. Take into account your needs and goals to make the best decision. • Deploy and Monitor It's time to implement your sustainable and self-sufficient solution once it has been created. You can make sure your models continue to function well by monitoring them after deployment. Never forget to keep an eye on the situation. www.nidmindia.com

12. Conclusion Nowadays, a lot of people are curious about "how to build an AI". To build an AI, you must first determine the issue you're attempting to solve, gather the appropriate data, develop algorithms, train the AI model, select the appropriate platform, choose a programming language, and, at last, deploy and oversee the performance of your AI system. www.nidmindia.com

13. THANK YOU +91 9611361147 nidmindia@gmail.com www.nidmindia.com