Simple, plain-English explanations accompanied by math, code, and real-world examples.
Part 1: Why Machine Learning Matters. The big picture of artificial intelligence and machine learning — past, present, and future.
Part 2.1: Supervised Learning. Learning with an answer key. Introducing linear regression, loss functions, overfitting, and gradient descent.
Part 2.2: Supervised Learning II. Two methods of classification: logistic regression and SVMs.
Part 2.3: Supervised Learning III. Non-parametric learners: k-nearest neighbors, decision trees, random forests. Introducing cross-validation, hyperparameter tuning, and ensemble models.
Part 3: Unsupervised Learning. Clustering: k-means, hierarchical. Dimensionality reduction: principal components analysis (PCA), singular value decomposition (SVD).
Part 4: Neural Networks & Deep Learning. Why, where, and how deep learning works. Drawing inspiration from the brain. Convolutional neural networks (CNNs), recurrent neural networks (RNNs). Real-world applications.
Part 5: Reinforcement Learning. Exploration and exploitation. Markov decision processes. Q-learning, policy learning, and deep reinforcement learning. The value learning problem.
Appendix: The Best Machine Learning Resources. A curated list of resources for creating your machine learning curriculum.
It is a common problem in Android development when your API is not sending you exactly the same data, what you want to show in your views, so you need to implement more complex requests. Possibly your app needs to make multiple requests, that wait for each other, or call multiple requests after the previous one finished. Sometimes you even need to combine these two approaches. This can be challenging in plain Java and will often result in unreadable code, what is also painful to test.
Today I’m going to show you in a simple example how this can be achieved in a clean way using RxJava. The example is written in Kotlin, what makes the code more concise and easy to read. If you are completely new to RxJava or Kotlin, I suggest you catch up on the basics. There are some great resources here as well.
- Read the pcap package, print the detailed icmp / tcp / udp protocol
- Read the pcap package or the network interface
Print detailed tcp session / udp message data, the current support mysql / pgsql / smtp / ftp / redis / mongodb authentication protocol analysis, http / dns complete protocol resolution.
To celebrate the publication of the eBooks of The Art of Computer Programming, (TAOCP), we asked several computer scientists, contemporaries, colleagues, and well-wishers to pose one question each to author Donald E. Knuth. Here are his answers.
Last year I wrote Blueprints for Up, describing how most of the building blocks are available to create a great serverless experience on AWS with minimal effort. This post talks about the initial alpha release of Up.
The TL;DR was to run your “vanilla” HTTP server inside of Lambda on a unprivileged port, and relay requests to it, so that you don’t have to write code specifically targeting Lambda or other platforms.
Roughly a month ago I decided to start working on it over at apex/up, and wrote the first small serverless sample application tj/gh-polls for live SVG GitHub user polls. It worked well and costs less than $1/month to serve millions of polls, so I thought I’d go ahead with Up and see if I can offer open-source and commercial variants.
The long-term goal is to provide a “Bring your own Heroku” of sorts, supporting many platforms. While PaaS is nothing new, the serverless ecosystem is making this kind of program increasingly trivial, however AWS and others often suffer in terms of UX due to the flexibility they provide. Up aims to abstract platform internals away and provide a user-friendly solution.