Hi All,

I am a scientific researcher working on areas like nanotechnology, quantum physics etc. I dont have any basic knowledge about python or any other language. How can I learn how to do scientific simulations using tensor flow ? Do I have to first learn Python or any other computer language ? Is there any expert here on this discussion forum who can help me to teach and help me to scientific simulations using tensor flow? My email is *Removed by moderator*

Hi @Akshaya_Rath. FWIW As your own question suggests there are different aspects/layers into your question. Maybe one first thing is to make sure Tensorflow is the right toolkit for the kind of models you develop?

Hello , kindly explain it in detail.

Yes I am sure, the Tensor Flow is the right tool kit for my scientific research. Kindly advise me how to proceed. I am from electrical engineering background and doing a research work that involves NANOTECHNOLOGY, OPTOELECTRONIC, QUANTUM PHYSICS, etc.

doing a research work that involves NANOTECHNOLOGY, OPTOELECTRONIC, QUANTUM PHYSICS, etc.

It is wide!

Anyways, If I were you I would start with learning a bit of Python, e.g. following a MOOC on Coursera and the like,

Then you can go through the many Tensorflow examples, notebook and the online documentation to get some familiarity with this framework.

And, at some point during your learning course you will feel comfortable enough to implement the model you need for your research.

Yes, using the AI tools like the tensor flow, I want to simulate my project related topics. Can some one guide me and join me to learn the basics of tensor flow? Does one need to start with Python ? please let me know.

More specifically, regarding the use of tensor flow for my research related areas, I got the following info from Google bard-: The IBM Deep Learning with TensorFlow course can help researchers in fundamental research areas like unification of gravity with electromagnetism in a number of ways.

It can be used to develop new theoretical models of gravity and electromagnetism. For example, researchers could use TensorFlow to simulate the behavior of particles and fields in different gravitational and electromagnetic fields.

It can be used to analyze experimental data from experiments on gravity and electromagnetism. For example, researchers could use TensorFlow to identify patterns and correlations in data that could be used to test new theories of gravity and electromagnetism.

It can be used to design new experiments on gravity and electromagnetism. For example, researchers could use TensorFlow to simulate the behavior of experimental apparatus and to optimize the design of experiments to maximize the amount of data that can be collected.

The IBM Deep Learning with TensorFlow course can also help researchers develop nano-superstructures, plasmonic nanostructures and nonlinear optical metamaterials having negative refractive index.

It can be used to simulate the behavior of these materials at the nanoscale. For example, researchers could use TensorFlow to simulate the scattering of light by nano-structures and to predict the properties of these materials.

It can be used to design new nano-structures and metamaterials with desired properties. For example, researchers could use TensorFlow to optimize the design of nano-structures to maximize their optical properties.

It can be used to analyze experimental data from experiments on nano-structures and metamaterials. For example, researchers could use TensorFlow to identify patterns and correlations in data that could be used to improve the design of these materials.

Finally, the IBM Deep Learning with TensorFlow course can also help researchers design lossless resonant systems.

It can be used to simulate the behavior of these systems at the nanoscale. For example, researchers could use TensorFlow to simulate the propagation of light through resonant systems and to predict their properties.

It can be used to design new resonant systems with desired properties. For example, researchers could use TensorFlow to optimize the design of resonant systems to maximize their efficiency.

It can be used to analyze experimental data from experiments on resonant systems. For example, researchers could use TensorFlow to identify patterns and correlations in data that could be used to improve the design of these systems.

Overall, the IBM Deep Learning with TensorFlow course can be a valuable tool for researchers working on fundamental research areas like unification of gravity with electromagnetism, nano-superstructures, plasmonic nanostructures and nonlinear optical metamaterials having negative refractive index, and design of lossless resonant systems. It can be used to develop new theoretical models, analyze experimental data, and design new experiments and materials.