2. ABOUT PROJECT
This project was totally based on machine learning, i.e., supervised
learning. The project was using CNN(convolutional neural network).
This project will be useful in recognizing different images easily. It
uses big data make machine learn.
Main objective of this project to make the machine learn so that it can
be used for training and education purposes.
The future scope of this project can be useful in many fields.
For example in medical, etc.
4. ALL ABOUT CNN
CNN is widely used in image and video
recognition.
CNNs like neural networks, are made up of
neurons with learnable weights and biases.
Each neuron receives several inputs, takes a
weighted sum over them, pass it through an
activation function and responds with an
output.
5. Supervised learning, in the context of artificial intelligence(AI) and machine learning, is a
type of a system in which both input and the desired output data are provided.
Supervised machine learning system provides the learning algorithms with known quantities
to support future judgement.
Chatbots, self-driving cars, facial recognition programs, expert systems ands robots are
among the systems that may use either supervised or un-supervised learning.
Supervised learning systems are mostly associated with retrieval-based AI but they may also
be capable of using a generative learning model.
ABOUT SUPERVISED LEARNING
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6. ABOUT PROJECT
Presentation title 6
Name: Image classifier
Platform: python with tensor flow using CNN
Guider: Mr. Arun K. Takuli sir
Location: G.L.bajaj institute of engineering and technology, Greater Noida, Uttar Pradesh
7. PURPOSE OF THIS PROJECT
Purpose of this project is that to learn how to make
machine learn, i.e., by using supervised learning using
CNN structure.
It is also helpful in many fields like medical, education,
etc. It uses big data to classify between the images and
the best part is that this can search images in offline
mode too.
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9. ABOUT FUTURE SCOPE
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• The future scope of this project is that, when the software is ready. Then then it can
be benificial to the state or the central government in tacking vehicles and people
and identifying objects.
• It can help in surgeries, reprogramming defects in human DNA, diagnosing medical
conditions, automatic driving in all forms of vehicles.
• The future image classification techniques helps in scanning every human and
knowing the difference in everyone’s personality traits.
• It can help in preventing cancer from increasing.