IQ Training’s AI & Deep Learning with Tensorflow course will provide you with in-depth knowledge of deep learning libraries, Machine learning Paradigms, Neural Network Architecture. This course empowers you to master various concepts like vectorization, binary classification, artificial neural networks, and logistic regression. Our Industry experts designed in such a way that learners will easily understand and implement the concepts of deep learning, execute algorithms of deep learning, computational Graphs unfolding, Boltzmann Machines and Deep Belief Networks.

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2.  1. Deep Learning a Revolution in Artificial Intelligence
 2. What is Deep Learning?
 3. Advantages of Deep learning over Machine Learning
 4. Where is Machine Learning being used?
 5.Limitations Of Machine Learning ?
 6. What is AI and Why AI?
 7. Pros and Cons of Artificial Intelligence
 8. Applications of AI in everyday Life
 9.Summary

3.  Billions of dollars are being invested in ML projects.
Because it is a centerpiece of digital transformation.
Deep learning is a major part of the machine learning
family. In the early 2000s, the impact of deep learning
in the industry has begun. In 2010 Deep learning large
scale speech recognition has started. Image net Victory
is the best example that shows the start of a Deep
learning Revolution that has transformed the AI
Industry.

4.  Deep learning works on the neural networks and it is a
part of machine learning algorithms. it works on the
multiple layers to extract the output from raw input,
Simply like in Image processing techniques.

6.  1. Medical Diagnosis
 2. Image Processing
 3. Prediction
 4. Virtual Personal Assistants (Siri, Alexa, Google)
 5. Video Surveillance
 6. Social Media Services
 7. Online customer support
 8. Search Engine results in refining etc

7.  1. It requires significant amount of data
 2. It may not work in cases where data collection is
difficult
 3. Limited understanding of the Black Box
 4. Data Acquisition
 5. High Error susceptibility
 6. Interpretation of results

8.  Artificial Intelligence is defined as a branch of
computer science that deals with the simulation of
intelligent behavior in computers which is nothing but
machines imitating human behavior and nature.
 As the need of technology increases day to day there
becomes a major issue in manpower, to overcome this
we need a machine which is similar to human behavior
and nature that is capable to perform all kinds of tasks
so that work may become so easier and accurate,
keeping in mind Artificial Intelligence revolution has
started, after that u all know the rest is history.

9.  Pros
 1. It gives accurate decisions
 2. Better handling of information
 3. Converts Information into Knowledge
 4. Rational Decision maker
 5. It does not wear out so easily
 6. Less room for errors
 7. It can work continuously without breaks
 Cons
 1. Expensive to maintain
 2. Expensive to implement
 3. Human work is replaced which leads to unemployment
 4. Work depends on machine
 5. Work is restricted up to some extents
 6. Lacks in creativity

10.  1.Banking sectors
In Banking sectors, AI is used for detecting suspicious activities in
ATM machines
2. Health/Medical Industry
AI In Health care is used for assisting Doctors. It automatically
detects and identifies potential abnormalities in CT/ MRI / X-ray
scans.
 3. Automobile Industry
In the Automobile industry for advanced features like vehicle
safety assistance checking, road tests, etc

11. 4.Government sectors:-
To identify and eradicate cyber attacks
5.Other Services
a. Predicting pricing patterns in ( Tickets, Travels,
Movie Theaters, etc)
b. Educational systems to implement automatic
grading and marks.
c. In Robotics, Data mining, Image processing,
Sports, and Text analysis, etc
d. Text-to-speech, Speech-to-text, Virtual personal
assistants, Visualization, etc

12.  This brings us to the end of this PPT on AI and
Deep Learning. In this PPT you have learn the
latest versions of AI. We have also come up
with a curriculum that covers exactly what you
would need to be expert in AI and Deep
Learning with Tensor Flow! You can have a
look at the course details for AI and Deep
Learning training with Tensor flow.

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