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This Notebook demonstrates modelling regression problems using Neural Networks with TensorFlow. Neural Networks can approximate non-linear relationships within dataset.They can be used for regression problems as well as classification problems.
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This post demonstrate the fundamental concepts in TensorFlow. TensorFlow is an end-to-end open souce Machine learning framework developed by Google. It can be used to implement complex deep learning models using inbuilt methods. It also blends very nicely with NumPy so we can use the Numpy Arrays in TensorFlow. This is one of the first post in the Deep learning with TensorFlow series.
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This notebook demonstrates, how to build a logistic regression classifier to recognize cats. This notebook will step you through how to do this with a Neural Network mindset, and will also hone your intuitions about deep learning.
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This tutorial demonstrates data analysis using example from two data sets using the Pandas Library. All the important operations are described in markdown cells.
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Numpy is a python library used to create, modify and interact with Arrays. It is a very vast and powerful library which is very essential for data analysis tasks. The Numpy library basic routines are very simple and easy to learn. Numpy is also known for scientific computation since it can handle large amount of data in the form of arrays.
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Basic Python Tutorial covering syntax of python and basic operations in python.