basezz.com

https://www.autobidmaster.com/en/carfinder-online-auto-auctions/?q=ferrari

https://www.hausatop.com/promote-your-music/

https://www.nobedad.com/article/about-izyblow/c=1fbe7e474d&nc=1

https://inaaija.wordpress.com/2015/01/19/home-localgunmen-kill-pregnant-woman-2-others-in-bauchi-cut-womans-hand-off/

f Online Advertising, Google PPC, AdWords Campaign, Mobile Ads Susan Li Dec 8 In Internet marketing, click-through rate (CTR) is a metric that measures the number of clicks advertisers receive on their ads per number of impressions . Mobile has become seamless with all channels, and mobile is the driving force with what’s driving all commerce. Mobile ads are expected to generate $1.08 billion this year, which would be a 122% jump from last year . In this research analysis, Criteo Labs is sharing 10 days’ worth of Avazu data for us to develop models predicting ad click-through rate (CTR). Given a user and the page he (or she) is visiting. what is the probability that he (or she) will click on a given ad? The goal of this analysis is to benchmark the most accurate ML algorithms for CTR estimation. Let’s get started! The Data The data set can be found here . Data fields id: ad identifier click: 0/1 for non-click/click hour: format is YYMMDDHH, s

I wanted to provide a simple, neat guide for starters to get hands-on MS Power BI and execute a dataset using the visualization in Power BI. Here is an approach I came up with today, using simple tools and methods. For Windows devices: Go to the Microsoft application store and get Power BI desktop Power BI desktop from Microsoft Store (Instead of Launch, you should have a Get button) Download and launch it in your system You might see this dialog box opened. We need to select Get data option here, and navigate to the dataset downloaded. But before that, we need to download a dataset to explore with Power BI. Once we download the dataset, we can come back to this step. I wanted to test on a World Satellite dataset. Union of Concerned Scientists provides a very nice and clean dataset in all formats : excel/csv/text file for all satellite launches. So I went on to download some datasets from their website with the following link (a website screenshot is provided

scraper in Python! — part II (EDA) Fábio Neves Nov 16 This article is a follow-up on another one where I built a web scraper to look for houses for sale in Lisbon. This time, I will focus on the transformation and cleaning process of the dataset we gathered before. I will then attempt to perform some exploratory data analysis (EDA) on the dataset. My goal is to give you some examples of what can be done, and… 3

I recently read this article on how to create a heat-map from your Google Location History data. Trying it out myself, I got some amazing results: The large red circles represent the cities I have spent a significant amount of time. The purple shade in different places represents places I had travelled to or passed through while on a train journey. My previous phone had some GPS issues, which was leading to my location being shown in Arizona, USA!. Surprisingly (or not?) it even gave a proof of that! All this was really cool to look at, but I really wanted to dive in and get some more insights into my travelling patterns throughout the years. Data Pre-Processing Like most data science problems, data pre-processing was definitely the pain point. The data was in a JSON format where the meaning of different attributes wasn’t very clear. Data Extraction {'timestampMs': '1541235389345', 'latitudeE7': 286648226, 'longitudeE7&#

Detecting multiple objects in images and tracking them in videos Chris Fotache Dec 10 In my previous story, I went over how to train an image classifier in PyTorch , with your own images, and then use it for image recognition. Now I’ll show you how to use a pre-trained classifier to detect multiple objects in an image, and later track them across a video. What’s the difference between image classification (recognition) and object detection? In classification, you identify what’s the main object in the image and the entire image is classified by a single class. In detection, multiple objects are identified in the image, classified, and a location is also determined (as a bounding box). Object Detection in Images There are several algorithms for object detection, with YOLO and SSD among the most popular. For this story, I’ll use YOLOv3 . I won’t get into the technical details of how YOLO (You Only Look Once) works — you can read that here  — but focus in