from 244 websites and represents 12,999 posts in total from a specific window of 30 days. The data was pulled using the webhose.io API, and because it's coming from their crawler, not all websites identified by their BS Detector are present in this dataset. Data sources that were ...
download a dataset !kaggle competitions download -c [name-of-the-competition] In this case datasets won't appear in your google drive, they will only be on the VM (and removed after 12 hours) in .kaggle/competitions/[name-of-the-competition] folder. One can specify folder on the mounted...
Section 6: Opening Webcam Using OpenCV Lecture 8 Opening Webcam Using OpenCV Section 7: Playing Video Using OpenCV Lecture 9 Playing Video Using OpenCV Section 8: Finding & Downloading Fire Dataset From Kaggle Lecture 10 Finding & Downloading Fire Dataset From Kaggle Section 9: Training Fire Dete...
and speed limit check. In addition, you will also learn how empty parking lot detection systems work. This section will cover the full process from data collection to parking occupancy classification. Before starting the project, we will download a training dataset from Kaggle, the dataset contains...
# TODO: returning a dict can make thing easier and cleaner when using dataset in training # but I don't know if this will slow down a little bit. new_batch = {} keys = batch[0].keys() values = list(zip(*[list(b.values()) for b in batch])) 2 changes: 1 addition & 1 del...
You get your hands on real projects, data, you build real applications, you use the model to run on your own dataset。 The book covers most of the fields in ML, from traditional supervised and unsupervised learning to deep learning like Neural network, This is the first time I review a ...
You will get a practical understanding of deep learning models with their architectures to understand their strengths and weaknesses。 Every Deep Learning model is implemented with a relevant dataset and problem to be solved。 By the end of this book, you will know the main difficulties that you...
dataset from Kaggle, Once, everything is ready, we will enter the main section of the course which is the project section The project will be consisted of three main parts, the first part is the data analysis and visualization where you will explore the dataset from multiple angles, in the...
using OpenCV. In this case, we will obtain a dataset from Kaggle and use that data to train the model to be able to detect emotion and facial expression. Then, in the third project section, we will build an age detection system using OpenCV. We will use a dataset containing photos of ...
Understanding Python is one of the valuable skills needed for a career in Deep Learning. Though it hasn’t always been, Python is the programming language of choice for data science. Here’s a brief history: In 2016, it overtook R on Kaggle, the premier platform for data science competition...