How TensorFlow Came To Be the Most Important Library in Machine Learning

How TensorFlow Came ...

  Two years ago, Google released to the public open-source software and deep-learning library TensorFlow. The immensely powerful tool has been driving the popularity of deep-learning since its debut and has also achieved the status of most forked repository on Github.   After a spike in interest in library’s initial release, we can see it’s […]

Time series classification with Tensorflow

Time series classifi...

Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems usually requires manual engineering of features which can then be fed into a machine learning algorithm. Engineering of features generally requires some  domain knowledge of the discipline where the data has originated from. For example, […]

How I Used Deep Learning To Train A Chatbot To Talk Like Me (Sorta)

How I Used Deep Lear...

Introduction Chatbots are “computer programs which conduct conversation through auditory or textual methods”. Apple’s Siri, Microsoft’s Cortana, Google Assistant, and Amazon’s Alexa are four of the most popular conversational agents today. They can help you get directions, check the scores of sports games, call people in your address book, and can accidently make you order a $170 dollhouse. These products all […]

Factorization Machines for Recommendation Systems

Factorization Machin...

As a Data Scientist that works on Feed Personalization, I find it it important to stay up to date with the current state of Machine Learning and its applications. Most of the time, using some of the better-known recommendation algorithms yields good initial results; however, sometimes a change in the model is essential to provide customers […]

Handwritten digits recognition using Tensorflow with Python

Handwritten digits r...

The progress in technology that has happened over the last 10 years is unbelievable. Every corner of the world is using the top most technologies to improve existing products while also conducting immense research into inventing products that make the world the best place to live. Some of these are the Amazon just walk out […]

How NOT to program the TensorFlow Graph

How NOT to program t...

Using TensorFlow from Python is like using Python to program another computer. Some Python statements build your TensorFlow program, some Python statements execute that program, and of course some Python statements aren’t involved with TensorFlow at all. Being thoughtful about the graphs you construct can help you avoid confusion and performance pitfalls. Here are a […]

TensorFlow and Queues

TensorFlow and Queue...

There are many ways to implement queue data structures, and TensorFlow has some of its own. FIFO Queue with a list In Python, a list can implement a first-in first-out (FIFO) queue, with slightly awkward syntax: >>> my_list = [] >>> my_list.insert(0, 'a') >>> my_list.insert(0, 'b') >>> my_list.insert(0, 'c') >>> my_list.pop() 'a' >>> my_list.pop() 'b' […]

Use only what you need from TensorFlow

Use only what you ne...

There isn’t just one decision to use TensorFlow or not use TensorFlow; you have to make decisions about which pieces of TensorFlow you’re going to use. I’ve thought about whether Tensorflow suffers from the second-system effect, and my conclusion is that while TensorFlow has a huge abundance of features, it can’t really be said to […]

Experiment with Dask and TensorFlow

Experiment with Dask...

This post briefly describes potential interactions between Dask and TensorFlow and then goes through a concrete example using them together for distributed training with a moderately complex architecture. This post was written in haste, see disclaimers below. This work was originally at matthewrocklin.com and is supported by Continuum Analytics and the XDATA Program as part of the […]