Machine Learning (ML): ML involves algorithms that learn from data and make predictions based on patterns in the data. It does not require large amounts of data and can operate on traditional computational methods. Deep Learning (DL): DL is a subset of ML that uses neural networks with many layers (hence ”deep”) to learn from large amounts of unstructured data. It is particularly useful in tasks like image and speech recognition but requires more data and computational power.
Consider the following two documents:
Document 1: ML and DL are part of AI.
Document 2: DL is a subset of ML.
Implement all four steps of the Bag of Words (Bow) model to create a document vector table .Depict the outcome of each step
There is a circular park of diameter 65 m as shown in the following figure, where AB is a diameter. An entry gate is to be constructed at a point P on the boundary of the park such that distance of P from A is 35 m more than the distance of P from B. Find distance of point P from A and B respectively.
You have three aqueous solutions A, B, and C as given below:
A - Potassium nitrate
B - Ammonium chloride
C - Sodium carbonate
The ascending order of the pH of these solutions is: