In today's newsletter, we'll cover a range of topics. You will learn about Free Data science books, ChatGPT, Big Data industry predictions, Flutter, writing Python code, AiOps plarforms, Top 100 Ai companies, DAM trends Choosing BI solution, Flutter, ML Algorithms cheat sheets, Python tips & tricks, DAM, Free NoSQL databases and usefull tools. We hope you enjoy it! Here are the top free Data Science Books for students and people must add to their list in 2023 in order to improve data science skills and to get data science jobs. ChatGPT and GPT-3 are both large language models trained by OpenAI, but they have some key differences.

These are all for personal use only, don't share them directly on social media. Also, most of them are wikis, please consider buying the book or donate to support the authors if you like them.

"Data indeed is the new oil" When I heard this for the first time many years ago, I mocked and ignored the statement. And, I am pretty sure many people like me are now thinking about how accurate this statement was. Currently, Data science has taken over all the industries without leaving any stones unturned. Every firm is trying to leverage a panoply of data at each and every step of its operations to obtain ultimate efficiency. It only makes sense for people to familiarize themselves with at least basic algorithms and tools to analyze the data in their respective domains to better understand the trends and in turn, make better decisions.

These three books by highly respected academics / practitioners, and cover some of the most popular techniques in data mining and machine learning today. The previous section, Statistical Machine Learning, covers machine learning from the perspective of statisticians: creating statistical valid models of the data that can be used for predictions. This section, practical machine learning / data mining, deals more with the need to extract information and make predictions from large datasets. The first book, [ADVANCED] Mining of Massive Datasets, is based off of Stanford's eponymous class, and covers popular problems such as recommendation systems, PageRank, and social network analysis. The second book, [ADVANCED] Deep Learning, has draft chapters available for free.

Now that Christmas and the New Year are behind us the nights are becoming a little longer with each passing day. Nevertheless, there's still loads of cold winter nights left to endure (unless you're in the Southern Hemisphere, in which case – throw me a shrimp on the barbie!). It's time to dust off your New Year resolutions from last year (remember those?) and get ready for a new start, a new you and learn some new data skills. I've thrown together a collection of five excellent (and free!) Data Science eBooks for your Kindle to sharpen up your ninja skills while you're on the long commute to work. Just try not to read them while driving!

Very interesting compilation published here, with a strong machine learning flavor (maybe machine learning book authors - usually academics - are more prone to making their books available for free). Many are O'Reilly books freely available. Here we display those most relevant to data science. I haven't checked all the sources, but they seem legit. If you find some issue, let us know in the comment section below.

These three books by highly respected academics / practitioners, and cover some of the most popular techniques in data mining and machine learning today. The previous section, Statistical Machine Learning, covers machine learning from the perspective of statisticians: creating statistical valid models of the data that can be used for predictions. This section, practical machine learning / data mining, deals more with the need to extract information and make predictions from large datasets. The first book, [ADVANCED] Mining of Massive Datasets [Check price on Amazon], is based off of Stanford's eponymous class, and covers popular problems such as recommendation systems, PageRank, and social network analysis. The second book, [ADVANCED] Deep Learning [Check price on Amazon], has draft chapters available for free.

Very interesting compilation published here, with a strong machine learning flavor (maybe machine learning book authors - usually academics - are more prone to making their books available for free). Many are O'Reilly books freely available. Here we display those most relevant to data science. I haven't checked all the sources, but they seem legit. If you find some issue, let us know in the comment section below.

Very interesting compilation published here, with a strong machine learning flavor (maybe machine learning book authors - usually academics - are more prone to making their books available for free). Many are O'Reilly books freely available. Here we display those most relevant to data science. I haven't checked all the sources, but they seem legit. If you find some issue, let us know in the comment section below.