Statistical Data: Your Self-Learning Plan
As you are aware, AI analyses data of multiple kinds!
Let us understand this in 4 easy steps.
Let us understand this in 4 easy steps.
- We talked about Videos and Images in CV
- Text and Speech in NLP,
- Numbers, data like price history, share market data, weather, or migration data. These are numerical data and come under the broad category of Statistical Data.
Statistical Data: Real Life Examples
AI tries to find a typical pattern in the set of numbers provided as the training data. These patterns are further used to deduce trends and take decisions. Just like the real-life examples below:
- Using the flight records, migration data, news articles from across the world, .
- Statistical Data is being leveraged to work out agricultural decisions, market
Let us get to know about statistical data more with the help of an example.
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), India, developed a sowing app which comprises of information such as:
- Sowing recommendation,
- Seed treatment,
- Optimum sowing depth,
- Preventive weed management,
- Land preparation,
- Farmyard manure application,
- Advice on harvesting,
- Shade drying of harvested pods,
- Storage, and more.
The major task that AI did, was to analyze data of sowing patterns over the years, their expected and actual yields, and other inputs.
It was later seen that if farmers followed the sowing app’s predictions, the yields increased by 30%.
It was later seen that if farmers followed the sowing app’s predictions, the yields increased by 30%.
Search 'Online Football Predictions'।
- See how machine learning can predict football match results
- For example, Kickoff.ai
Search 'AI Rock, Paper, Scissors'
- Go ahead and play rock paper scissors online, with your AI buddy
- For example, infinity rock paper scissors