"What we want is a machine that can learn from experience" There is no doubt that Machine Learning has become one of the most popular topics nowadays. According to a study, Machine Learning Engineer was voted one of the best jobs in the U.S. in 2019. Looking at this trend, we have compiled a list of some of the best (and free) machine learning books that will prove helpful for everyone aspiring to build a career in the field. Even paid books are seldom better. A good introduction to the Mathematics, and also has practice material in R. Cannot praise this book enough.

"What we want is a machine that can learn from experience" There is no doubt that Machine Learning has become one of the most popular topics nowadays. According to a study, Machine Learning Engineer was voted one of the best jobs in the U.S. in 2019. Looking at this trend, we have compiled a list of some of the best (and free) machine learning books that will prove helpful for everyone aspiring to build a career in the field. Even paid books are seldom better. A good introduction to the Mathematics, and also has practice material in R. Cannot praise this book enough.

Can you help us know about your professional background? I completed my engineering from BITS Pilani in 2012. Immediately after that I joined Opera Solutions as a Data Scientist. During my stint at Opera Solutions I met my co-founders Angam and Ankit, and decided to explore entrepreneurship. We started by building a news recommendation engine in early 2014.

"What we want is a machine that can learn from experience" There is no doubt that Machine Learning has become one of the most popular topics nowadays. According to a study, Machine Learning Engineer was voted one of the best jobs in the U.S. in 2019. Looking at this trend, we have compiled a list of some of the best (and free) machine learning books that will prove helpful for everyone aspiring to build a career in the field. Even paid books are seldom better. A good introduction to the Maths, and also has practice material in R. Cannot praise this book enough.

Machine learning has made it more accessible to create meaningful insights in a data-rich world. This includes data from customer surveys, qualitative primary research, and online verbatim comments. There is a wide range of input that arises in the lifetime of a business. This data needs to be mined for actionable insights, that can significantly impact the brand value of a business. You could have launched a new marketing campaign and want to review customer sentiment.

Natural Language Processing (NLP) is the ability of a computer system to understand human language. Natural Langauge Processing is a subset of Artificial Intelligence (AI). There are multiple resources available online which can help you develop expertise in Natural Language Processing. In this blog post, we list resources for the beginners and intermediate level learners. A beginner can follow two methods i.e.

The internet is filled with tutorials to get started with Deep Learning. You can choose to get started with the superb Stanford courses CS221 or CS224, Fast AI courses or Deep Learning AI courses if you are an absolute beginner. All except Deep Learning AI are free and accessible from the comfort of your home. All you need is a good computer (preferably with a Nvidia GPU) and you are good to take your first steps into Deep Learning. This blog is however not addressing the absolute beginner.

Data science is an inter-disciplinary field which contains methods and techniques from fields like statistics, machine learning, Bayesian etc. They all aim to generate specific insights from the data. In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science. This data science book is a great blend of lectures in the modern theoretical course in data science. This tutorial aims to get you familiar with the main ideas of Unsupervised Feature Learning and Deep Learning.

The revolution of the web has led to an explosion of content generated every day on the internet. Social sharing platforms such as Facebook, Twitter, Instagram, etc. have seen astonishing growth in their daily active users, but have been at their split ends when it comes to monitoring the content generated by users. Users are uploading inappropriate content such as nudity or using abusive language while commenting on posts. Such behavior leads to social issues like bullying and revenge porn and also hampers the authenticity of the platform. However, the pace at which the content is generated online today is so high that it is nearly impossible to monitor everything manually.

Web 2.0 revolution has led to the explosion of content generated every day on the internet. Social sharing platforms such as Facebook, Twitter, Instagram etc. have seen astonishing growth in their daily active users but have been at their split ends when it comes to monitoring the content generated by their users. Users are uploading inappropriate content such as nudity or using abusive language while commenting on posts. Such behavior leads to social issues like bullying and revenge porn and also hampers the authenticity of the platform. However, the pace at which the content is generated online today is so high that it is nearly impossible to monitor everything manually.