Since the uprising of Artificial Intelligence, text classification has become one…
In Part 1, we left after deriving basic equations for a Kalman filter algorithm. Here…
There’s two ways to predict a stock, one is predicting the actual value into an x amount of time into the future, which is usually graphed and this is mainly what you’ll see compared with the “actual value” which is mainly the test set vs. the prediction graphed, which usually is…
Weekend of a Data Scientist is series of articles with some cool stuff I care about. Idea is to spend weekend by learning something new, reading and coding.
You will never miss your package again!
In this article, I will share with you the steps to build a real-time object detection system to detect FedEx/UPS/USPS delivery…
Notebooks are one of the most powerful tools in the arsenal of a data scientist…
By Ian Blumenfeld, Chief Data Scientist, and Brian Johnson, Senior Engineer at Clover Health Since…
Let’s start by defining a typical speech recognition problem. Suppose we have a dataset of…
In the last part I talked about how CTC can be used to map speech input to its corresponding transcript and discussed about the CTC model…
Our brains have a capacity which artificial neural networks still lack: we can form analogies, relating disparate inputs and processing them using the same heuristic. The official lingo is ‘transfer learning’. Fundamentally, analogies are a form of compression…
In this article, we will dive more into the world of ML. We’ll be studying different algorithms and the way…
Li Deng’s journey with AI has spanned for more than 3 decades. After working as…
“No podemos evitar las Fake News, solo combatirlo para minimizar su impacto.”
In today’s machine learning techniques, these are indispensable tools used to train models. Each sort…
Does insurance have a fairness problem? The use of credit scores to set auto insurance premiums is a prime example of how non-driving factors push up costs for those who can least afford them.
In natural language discourse, speakers and writers often rely on implicit, “common sense” inference to signal the kind of contribution they are making to the conversation, as well as key relationships that justify their point of view. The…
From June 2020, I will no longer be using Medium to publish new stories. Please, visit my personal blog if you want to continue to read my articles: https://vallant.in.
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“Data is the new oil. We need to find it, extract it, refine it, distribute it and…
This summer, I got an opportunity to intern at Nodeflux, an Intelligent Video Analytic company…
This is my guide of how I took my first steps and developed a full learning plan.
It is possible to build a model that represents the training data perfectly. If a predictive or discriminatory function is desired, the desired model must represent unseen data accurately. Regularization is the process that simplifies a model, to allow it to more accurately describe the entire dataset.
Here, I’m gone show you how to predict your train ticket will be confirmed or not
This is how the ticket looks like. This ticket is not confirmed by railway, because, lot of tickets are in queue.
In Context episode 10 featuring Len D’Avolio
In this episode of the In Context podcast, we welcome Len D’Avolio. Len is Co-Founder and CEO of Cyft, a Boston-based machine learning startup…
When you talk to your Alexa, Google assistant or Siri, your voice is recorded and sent to the…
We are in a war of attention, with thousands of engineer optimized apps and gizmos attempting to steal your precious time. We are so caught up…
I am a kernels expert at kaggle and I will recommend this article to anyone and everyone. Truer description of kaggle has not been seen. Very insightful article with just the amount of things needed to get motivated and get started on the data science journey.
CGI is playing an increasingly important role in contemporary culture. Filming for…
Hello,
Thanks for writing. In the word embedding world, words are represented by vectors with arbitrary length. Since a vector represents each word, its length can be any size, depending on the purpose or model. In Glove, the authors used the different corpus to learn word embeddings, and in each corpus, words are…
My dad has been bugging me to go for higher studies for some time now. So I have been coming up with…
Want to know more about the process behind this project? Check out Tony’s awesome tutorial.
Last week I came accross DynamoDB. Over the past few years I was fascinated by how the industry went from relational to nosql to newsql and then spread to all direction, collapse into mysql / postgres etc. The whole thing is both funny and…
An intelligence with the power to form analogies, which maps a description of a logic onto a simpler subsystem, can form paradox because it does not perform recursion on the logic — instead, higher-order assessments simply fail to settle upon a single answer, generating contradiction in every…
Audio classification is a very interesting problem because there is no correct answer or clearcut definition of a category. Many people classify music based on their own prefrence and sort it into their own playlists. Some songs may…
The recent surge of data has empowered a field of computer science that uses statistical techniques to give computer systems the ability to learn: machine learning. Modern machine learning algorithms are able to overcome strictly static program instructions and make data-driven…
Congrats. You’ve just completed your first course in Deep Learning. At this point, you have learned to:
I’ve written about this idea before, and probably will for a long time to come, but…
Artificial Intelligence (AI). Machine Learning (ML). Deep Learning (DL). You might come across these…
A lot of data in the real world can be represented as graphs: you have nodes connected…
Inventions based in artificial intelligence (AI) are very interesting because these inventions often incorporate a variety of inventive technologies. There is usually a physical device involved in an AI invention, such as a…
There are many ways you train machines every day. Every time you mark something as…
It all started with a goal of making bots sound so human that no one can identity them as bot. But soon we realized that its not a realistic goal.
With AI ethics and explainable Machine learning coming into focus, the aim is now…
圖中的節點被稱為op，一個op獲得0個或多個 Tensor執行計算，產生0個或多個 Tensor
Exercice :
z = 2exp(x*y+cosx²)
grad{x,y}(z) = ?
ML is applied in various fields covering everything from business to scientific research, like Logistics and supply chain, Workflow automation, Software security systems, Big Data processing and predicting, Training software, Medicine, Physical objects’ security systems, Customer interaction personalization, Smart cars, etc. https://jelvix.com/blog/machine-learning-use-cases
