Being ready with the development environment, let’s learn the most used machine learning algorithms and how to apply the

Until now, you have learned the basics. Depending on your education, you could have missed some basic concepts in mathematics, statistics, or computer science. For example, a computer science student could not know how to perform a Maximum Likelihood Estimation or a mathematics student could not know how to compute the complexity of an algorithm. It’s absolutely normal! Data Science is a very wide field and it is impossible to know everything!,Although the cases have yet to be formally linked, a Virginia Beach Spokesperson confirmed that the cases are similar, and a serial killer connection has been looked into. They stated that they are in the process of “connecting the dots.”,The operating system reads data in page granularity, meaning it can only read at a minimum 4kB at a time. That means if you need to read read 1kB split in two files, 512 bytes each, you are effectively reading 8kB to serve 1kB, wasting 87% of the data read. In practice, the OS will also perform read ahead, with a default setting of 128kB, in anticipation of saving you cycles later when you do need the remaining data. But if you never do, as is often the case for random I/O, then you just read 256kB to serve 1kB and wasted 99% of it.,It’s totally wrong! There is dense literature on this topic: how to train a neural network, which type of networks works in a particular contest, what is the hardware architecture required to train a neural network of a certain size. To start, you can take the courses from the Deep Learning Specialization while as a textbook check Deep Learning. Two of the most used frameworks for building artificial neural networks are TensorFlow and PyTorch. There are many materials online starting from their official websites.,Colab on steroids: free GPU instances with SSH access and Visual Studio Code Server A step-by-step guide to SSH into a free GPU instance provided by Google Colab and install Visual Studio Code Server.towardsdatascience.com,Basic mathematical courses include linear algebra, real analysis, and numerical analysis. Basic statistics courses include descriptive statistics, inferential statistics, bayesian statistics. Basic computer science concepts consist of: time and space complexity, data structure, sorting and searching algorithms, algorithms on graphs, and algorithm design. You can find all these arguments in any undergraduate coursebook. And of course, Google is your friend!,At this point, you should be confident in using main data science packages (for example, caret or scikit-learn). You can test the algorithms you have learned on some public datasets: UCI Datasets, Kaggle Dataset or find one on Google Dataset Search directly.,The girls had no enemies, there were no witnesses, and despite the Virginia Beach Police Department’s best efforts, the case went cold. At the time, police had no idea if it had been a targetted attack, random, or crime of opportunity.,Remember: data science is not only about models and performance! You could have the best idea in the world but you don’t know how to formalize it, you could be able to write the algorithm that solves every problem but the algorithm could be inefficient and requires too much resource to run. Knowing the basics of different fields will help you to deliver more effective solutions with actionable insights.,So if you arrived here, you already know a bunch of algorithms to build models, you are confident to develop a data science project with well-known packages and you already have an idea of how neural networks work. It’s time to have a full immersion into deep learning! The common misconception about deep learning is that it is just a series of layers of neurons that can be fit to predict anything, as magic.,DNA evidence is likely what police will use to connect those dots. In 2018, it was announced that there was a strong lead in the 1973 murders of Janice Pietropola and Lynn Seethaler. And in 2019, they made an arrest forty-six years after their murders. Eighty-two-year-old Ernest Broadnax was arrested in New York.,Custom neural networks in Keras: a street fighter’s guide to build a graphCNN How to build neural networks with custom structure and layers: Graph Convolutional Neural Network (GCNN) in Keras.towardsdatascience.com,Most of the time, the key component of a data science project is data visualization. A data scientist should be able to communicate its insights with effective plots or make the results usable by the business through a dashboard. If you are using Python, matplotlib, plotly, seaborn and streamlit are common choices. In R there are ggplot2 and Shiny Dashboard. If you like the hard way, you can try D3.js. You will find out that there are several data visualization solutions out there and it is impossible to learn to use all of them! My philosophy here is to learn just a couple of them to be ready to create a prototype to show the results. In many projects, the final data visualization solution is already chosen because part of an existent workflow and you only need to create endpoints to deliver the output of your models.,The women were all young, attractive, and the manner of their death seemed consistent. They all included sexual assault, strangulation, and extreme violence. Some women were murdered in their homes, and others were found in their cars or dumped on the beaches.,Although this was the first major homicide case in the area, it wouldn’t be the last. In the years following Janice and Lynn’s murders, ten more women either disappeared from the area or were murdered between 1974–1980.