All businesses introduce new products for various reasons. The new products poses challenge for the planners and marketing executives to estimate the demand for them for merchandise and supply planning purposes. The primary reason being the lack of historical data that can be used for forecasting. These techniques are'By Analogy' and'Bass Diffusion' including a live demonstration using a planning software. While Analogy is the more popular technique, the issue most planners face in this technique is in choosing the right analogue product.

With the acceleration and growth of technology we are in a new age. With technology like Natural Language Processing we are able to create and build applications that can change the world. We have the tools in the palm of our hands just need to understand how use them. Learn and build applications on one of the most cutting edge technology fields today with this easy to understand course on the Four Keys to Natural Language Processing. With this course you will be able to understand why NLP is a driving force to change the way we interact with computers, learn from data, and solve problems.

Data is becoming a force to recon with. With the amount of data that is being generated every minute, dealing with data has become more important. The importance of data lies in the fact that it allows us to look at our history and predict the future. Data Science is the field that deals with collecting, sorting, organizing and also analyzing huge amounts of data. This data is then used to understand the current and future trends.

The real power and value proposition of Apache Spark is its speed and platform to execute data processing and data science tasks. Let's see how easy it is! Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. Spark is one of the most widely-used large-scale data processing engines and runs extremely fast. It is a framework that has tools that are equally useful for application developers as well as data scientists.

Ahead of the event in May, we are taking a look at some the companies and people who are taking part in the massive unconference–an open space event with organization powered by participants. TechNode is organizing the Explore Expo, an exhibition area for young tech startups looking for exposure. The education industry is generally viewed as traditional, dogmatic, and oppressive in many Asian countries, especially in China. As China's edtech sector takes off and begins to attract a deluge of investment, tech companies are exploring more ways to spice up the learning experience. "The compulsory education system is rigid," Chu Liang, CTO of Ellabook, told TechNode, "but over the past decade, technology has been transforming many industries and sectors. Ellabook (咿啦看书) is an ebook reading platform, like Kindle, but for kids from 3 to 12 years-old. The app is animated and interactive, which encompasses a wide range of learning categories like reading skills, English, mathematics, and art.

This team has decades of practical experience in working with Java and with billions of rows of data. If you are an analyst or a data scientist, you're used to having multiple systems for working with data. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code. Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.

The course will mostly focus on helping you implement different statistical analysis techniques on your data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects immediately! TAKE ACTION NOW:) You'll also have my continuous support when you take this course just to make sure you're successful with it. If my GUARANTEE is not enough for you, you can ask for a refund within 30 days of your purchase in case you're not completely satisfied with the course.

Whatever be your motivation to learn Computer Vision, I can assure you that you've come to the right course. This course is tailor made for an individual who wishes to transition quickly from an absolute beginner to a Computer Vision expert in a few weeks. The most difficult concepts are explained in plain and simple manner using code examples. I personally guarantee this is the number one course for you. This may not be your first OpenCV course, but trust me - It will definitely be your last. I assure you, that you will receive fast, friendly, responsive support by email, and on the Udemy.

About this course: We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-performance predictions using Cloud Machine Learning Engine. Course Objectives: Create machine learning models in TensorFlow Use the TensorFlow libraries to solve numerical problems Troubleshoot and debug common TensorFlow code pitfalls Use tf.estimator to create, train, and evaluate an ML model Train, deploy, and productionalize ML models at scale with Cloud ML Engine

About this course: This course is an introduction into formal concept analysis (FCA), a mathematical theory oriented at applications in knowledge representation, knowledge acquisition, data analysis and visualization. It provides tools for understanding the data by representing it as a hierarchy of concepts or, more exactly, a concept lattice. FCA can help in processing a wide class of data types providing a framework in which various data analysis and knowledge acquisition techniques can be formulated. In this course, we focus on some of these techniques, as well as cover the theoretical foundations and algorithmic issues of FCA. Upon completion of the course, the students will be able to use the mathematical techniques and computational tools of formal concept analysis in their own research projects involving data processing.