Agility has been the subject of numerous theories, publications and conferences for several years. The concept was historically created during a gathering of software development experts in 2001. They explain the ins and outs of what we know as « agile » through a founding document called the “agile manifesto“, which encompasses 4 values and 12 principles. At the time, it was mainly a solution proposed by developers to manufacture a software in the most efficient way while guaranteeing its adequacy with the needs of the customer. 17 years later, things have changed, and the agile manifesto provides only part of the answers to bring out a new product or service with what specialists call a good time-to-market and a good product market fit in the digital age.
TensorFlow is a software library, open source since 2015, of numerical computation developed by Google. The particularity of TensorFlow is its use of data flow graphs.
Since the emergence of Taylorism and of the specialized worker executing one specific task, working methods never stopped to evolve. Nowadays, in the era of self-management, we make sure that every employee has been given the keys to participate in the decision making process and to perform his mission.
Today there is an increasing multiplication of concepts around the managing methods of development projects. But to succeed in adapting them to each context, it is important to first understand the basic principles.
Data Science is having an increasing impact on business models in all industries, including retail. According to IBM, 62% of retailers say the use of Big Data techniques gives them a serious competitive advantage. Knowing what your customer wants and when, is today at your fingertips thanks to data science. You just need the right tools and the right processes. We present in this article 10 essential applications of data science in the field of retail.
TalkingData, China’s largest independent big data service platform, covers over 70% of active mobile devices nationwide. Their current approach to prevent click fraud for app developers is to measure the journey of a user’s click across their portfolio, and flag IP addresses who produce lots of clicks, but never end up installing apps. While successful, they want to always be one step ahead of fraudsters and have turned to the Kaggle community for help in further developing their solution.