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.
Transfer Learning With MobileNetV2
In this notebook we will be learning how to use Transfer Learning to create the powerful convolutional neural network with a very little effort, with the help of MobileNetV2 developed by Google that has been trained on large dataset of images.
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.
Machine Learning in Java Book
It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life.
Smart Internet of Things Projects Book
Creating basic IoT projects is common, but imagine building smart IoT projects that can extract data from physical devices, thereby making decisions by themselves.
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.
Exploring the Tensorflow
Once you install the Tensorflow, that contains the wide variety of files and folders. Two top level folders are particularly important. The core directory and the contrib directory.
The Evolution of Machine Learning
The development of Machine Learning started from very early. Different scientists and researchers hard work and research made much Machine Learning possible in a way we are learning now.
Choosing a Classification Algorithm
Choosing a appropriate algorithm for classificaion of a particular problem task requires a lot of practice, each algorithms has its own quirks and is based on certain assumptions.
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.
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning Book
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work.
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.