Machine learning is a complicated discipline, but implementing machine learning has become easier as compared to it was before, thanks to the machine learning frameworks that are being used today, like Google Tensorflow. It is the process of getting the data, training the models, doing predictions, and giving a refined final result. Google developed this framework for machine learning as a combination of tensor and flow. Here tensor is nodes in the graph and their flow happens with the help of the edges. The representation of the vector or multi-dimensional arrays is known as the tensors. It combines digits to represent the data in the code form and is featured with an open-source library that helps you to implement machine learning. You can do powerful experimentation for your research after Tensorflow Online Training.
It simplifies the life of the users
Tensorflow relies on strong architecture to simplify the life of the users. It is comprised of three steps. The first step is data pre-processing which is a method of collecting unstructured data, structuring those data, and then bringing those under one limit value. Model building is the second step and training & estimating the models is the third in this regard.
It is an open-source platform
Being an open-source and community-driven platform, it is open for new advancements by the community, so always stays updated. This platform allows the developers to create machine learning applications using various tools, libraries, and community resources.
It is featured with Keras API
Owing to its Keras friendliness, it helps different combinations of inputs, outputs, and layers. It also ensures that it reduces memory allocations and makes memory allocation easier. AI and Deep Learning with TensorFlow training is designed to help the professionals to accelerate the work process of data collection and redefining data. It restores the workflow of artificial intelligence and Deep Learning with the use of Keras API.
It gives data visualization facility to the users
Graphical representation helps developers not to go back and look at the whole code for debugging. This open-source software library provides architectural TPU that is much faster than GPUs and powerful CPUs.
|Start Date||End Date||No. of Hrs||Time (IST)||Day|
|09 Dec 2023||31 Dec 2023||24||06:00 PM - 09:00 PM||Sat, Sun|
|16 Dec 2023||07 Jan 2024||24||06:00 PM - 09:00 PM||Sat, Sun|
|23 Dec 2023||14 Jan 2024||24||06:00 PM - 09:00 PM||Sat, Sun|
|30 Dec 2023||21 Jan 2024||24||06:00 PM - 09:00 PM||Sat, Sun|