In our last blog we discussed the importance of BigQuery and BigQuery ML, in order to fully understand the importance and usefulness of this, we need to introduce you to Tensorflow. Tensorflow is an inventive open-source software application, also developed by Google, which can be used to build and train Machine Learning (ML) models. We learned a bit about Machine Learning in our BigQuery blog, although now we’ll dig a bit deeper! Tensorflow is innovative in that it can make the process of gathering data, training models, evaluating and refining models, easier and quicker, here’s what you need to know!
We’re about to learn a few new terms, so get that thinking cap ready! Tensorflow uses both ML and deep learning to build models. Deep learning is an area of ML that focuses on building algorithms that mimic the functioning and structure of the human brain, using a technology known as artificial neural networks. This is some mind blowing technology development! Deep learning advances the field of ML and artificial intelligence by making it easier to understand and use different ML algorithms. In essence, deep learning can be defined as a large neural network. A neural network, also known as an artificial neural network, is another field in ML that specialises in deep learning. A neural network consists of three main layers, which consist of an input layer, one or more hidden layers, and finally an output layer. These layers are known as node layers and consist of artificial neurons, called nodes. Nodes have specific parameters associated with it, a threshold and a weight. The output of each node is evaluated against the threshold, and if the output is above the threshold, it is passed into the next layer, if not, the output does not pass through. Now we all know you can train a dog, or even a bird although when did we ever think training data would be possible?! Training data can be used to improve the accuracy of a neural network and fine-tune its associated parameters so that it can eventually be used as a powerful ML tool that can perform classification on complex datasets, quickly and effectively.
Tensorflow uses a similar structure to that of a neural network, consisting of an input, a flow of several operations and an output layer. Tensorflow uses multi-dimensional arrays, otherwise known as tensors, as its input. Tensors possess specific properties, such as a shape, i.e. a dimensionality, and a specific data-type that is consistent throughout the entire tensor. The structured flow used in Tensorflow makes it easier for users to visualise the computations of the algorithm. Computations are made using tensors and mathematical operations in nodes.
Each node, like in a neural network, represents a mathematical equation, otherwise known as operation, and is connected to other nodes using the data that flows. One of the special features in Tensorflow is its use of graphs. Graphs are a set of operations that have taken place successively on a specific input. Graphs represent the arrangement of nodes/operations of the model. This makes Tensorflow easy to use as users are able to visualise graph computations with neural networks, allowing users to spend less time focusing on the flow of the network and rather on the logic used.
Some of the benefits of Tensorflow include its incredible versatility, as it can be run on many different platforms and be trained on multiple machines. Tensorflow uses both GPUs and CPUs. GPUs, where available, can be used to perform computations fairly quickly. Users can monitor what Tensorflow is doing using Tensorboard which is a centralised dashboard, that allows users to easily track their model’s accuracy and visualise how parameters used in the model change overtime.
Tensorflow can be used to perform not only voice recognition, but image as well as text recognition! It can also analyse time-series data to build recommendation systems, such as those used in Google Search and Netflix. Tensorflow is extremely adaptable as it can be applied to many industries and can easily enhance any user’s experience.
This makes Tensorflow a huge asset to your company! Contact us today to discuss how Tensorflow can assist your company is massive ways! firstname.lastname@example.org