Is There a Standard Heuristic for Model Tuning?
Training error should steadily decrease, steeply at first, and should eventually plateau as training converges.If the training has not converged, try running it for longer.
Terms to remember while building a Machine Learning Model
There are different terms we should remember while training our machine learning model, so that we can use our machine learning model more effectively and properly.
Creating Tensors with different functions in Tensorflow
We can make the tensors from the known values. The tf package provides seven function which we can use to from tensors with known values. Constant,zeros,ones,fill etc.
Mining of Massive Datasets Book
This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets.
Data Mining: Practical Machine Learning Tools and Techniques Book
As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data.
A Roadmap For Building Machine Learning Systems
To develop a machine learning model there is roadmap which you can follow so that you can build the best model with the best accuracy.
Machine Learning in Action Book
Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis.
Linear, Higher and n-dimensional Space in Machine Learning
Usually refers to number of attributes.There are different types of dimension in which we can represent our data points.Linear,Higher,n-dimensional space.
Difference between Dimensions, Attribute and Feature in Machine Learning
Dimensions Usually refers to the number of attributes.Attributes Is one particular type of data in your points.Feature It may have multiple meaning depending on the context.
Building Machine Learning Systems with Python Book
Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation.
Machine Learning in Python Book
Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python.
Learning scikit-learn: Machine Learning in Python Book
Machine learning, the art of creating applications that learn from experience and data, has been around for many years.With Learning scikit-learn: Machine Learning in Python, you will learn to incorporate machine learning in your applications.