After losing his job…

Credits : Montreal in tech

Project Implementation

Pic credits : Pinterest
  • Flexible — Keras has simple workflows which are quick and easy
  • Powerful — Keras provides industry-strength performance and scalability

Importing important Libraries

%matplotlib inlineimport os
import numpy as np
import tensorflow as tf
from PIL import Image
from matplotlib import pyplot as plt
print('Using TensorFlow', tf.__version__)


generator = tf.keras.preprocessing.image.ImageDataGenerator(
rotation_range= 45

image_path = 'Path to image file'plt.imshow(plt.imread(image_path));

Credits: TechGig

Great Papers with Code…

Going Deeper with Convolutions

By Christian Szegedy • Wei Liu • Yangqing Jia • Pierre Sermanet • Scott Reed • Dragomir Anguelov • Dumitru Erhan • Vincent Vanhoucke • Andrew Rabinovich

Abstract —

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…

Great Papers…

Pic credits: Pinterest

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

By Andrew G. Howard • Menglong Zhu • Bo Chen • Dmitry Kalenichenko • Weijun Wang • Tobias Weyand • Marco Andreetto • Hartwig Adam

Abstract —

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…

Amazing papers…

Pic credits : Pinterest

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

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

Abstract —

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…

Amazing papers…

Pic credits : Pinterest

Qlib: An AI-oriented Quantitative Investment Platform

By Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu

Abstract —

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…

How UX design impacts SEO…

Photo: Unsplash (Image source and credits : Kelly Sikkema)
  1. Offer users the best possible experience
  2. List quality websites with good rankings

What is UX?

User Experience (UX) is very critical to the success or failure of a product or website in the market.

Priyesh Sinha

IITian| Mech Engineer| Pursuing Data Science Courses

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