The creator of Shopify, Tobi Lutke, a 37-year-old German immigrant who turned the tables by turning Shopify stocks into one of tech’s hottest stocks which went public on the NYSE in May 2015 at $17 per share, now trades at more 6 times times that price, was worth $1.1 billion from company shares and proceeds in late November.
But it didn’t start as shining as it looks. Tobi grew up in Germany, learned to code by age 12 and left school at 16 to enter a computer programming scholarship. Tobi founded the startup in 2004 when he hopelessly followed his…
Keras which runs on top of the machine learning platform TensorFlow is a deep learning API written in Python. It was developed with a focus on enabling fast experimentation.
%matplotlib inlineimport os
import numpy as np
import tensorflow as tffrom PIL import Image
from matplotlib import pyplot as pltprint('Using TensorFlow', tf.__version__)
generator = tf.keras.preprocessing.image.ImageDataGenerator(
)image_path = 'Path to image file'plt.imshow(plt.imread(image_path));
Python is one of the most widely used programming languages in the technology world. After completing the basics, you can start developing the projects to be able to get a grip and build a solid foundation.
This is the part 2 of best AI/ML research papers on object detection you must read. You can read the part 1 in the link given below —
Here we go —
By Christian Szegedy • Wei Liu • Yangqing Jia • Pierre Sermanet • Scott Reed • Dragomir Anguelov • Dumitru Erhan • Vincent Vanhoucke • Andrew Rabinovich
We propose a deep convolutional neural network architecture codenamed “Inception”, which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC 2014). The main hallmark of this architecture…
By Andrew G. Howard • Menglong Zhu • Bo Chen • Dmitry Kalenichenko • Weijun Wang • Tobias Weyand • Marco Andreetto • Hartwig Adam
We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks. We introduce two simple global hyper-parameters that efficiently trade off between latency and accuracy. These hyper-parameters allow the model builder to choose the right sized model for their application based on the constraints of the problem. We present extensive experiments on…
By Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela
Large pre-trained language models have been shown to store factual knowledge in their parameters, and achieve state-of-the-art results when fine-tuned on downstream NLP tasks. However, their ability to access and precisely manipulate knowledge is still limited, and hence on knowledge-intensive tasks, their performance lags behind task-specific architectures. Additionally, providing provenance for their decisions and updating their world knowledge remain open research problems. Pre-trained models with a differentiable access mechanism to explicit non-parametric memory can overcome…
By Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments. Recently, inspired by rapid development and great potential of AI technologies in generating remarkable innovation in quantitative investment, there has been increasing adoption of AI-driven workflow for quantitative research and practical investment. In the meantime of enriching the quantitative investment methodology, AI technologies have raised new challenges to the quantitative investment system. Particularly, the new learning paradigms for quantitative investment call for an infrastructure upgrade to accommodate…
Some people assume that Keywords + Meta Descriptions + Title Tags = Good website ranking.
But NO, the assumption is wrong!
There are 3.5 billion Google searches made each day. Google mines for data with every search which yields a whole lot of data and when it comes to search, Google has 3 critical objectives —
User Experience (UX) is very critical to the success or failure of a product or website in the market. …