20 years ago, the world was changing. Internet was a wild west. Brave scientist transformed the world forever. Today, Data Science is that new technology which will transform every single business in the next 10 years. Data is the power that's waiting to be discovered. It is the past, we look at, to understand the present and predict the future. 
Welcome to the Machine Learning Serbia podcast. My name is Manja Bogicevic, Machine Learning Entrepreneur and Author. Hello for my side, my name is Nikola Basta, Data Scientist, and Business Advisor. Each month, we will bring you inspiring people and ideas to help you build your successful business and career in data science. 
Does that sound exciting? Then, join us and let's create the future together

The present and future of Data Science

MLS 001: The present and future of data science with Nikola Basta and Manja Bogicevic

What a CEO needs to know about machine learning? How Machine Learning works. After that what you can do with it. In conclusion how to get started. Therefore, information on ML is often confusing and sometimes downright misleading. But ML for business is simple:
“99% of the economic value created by AI today is through one type of AI, which is learning A to B or input to output mappings.” Andrew Ng
Almost every business application of ML today is about learning to produce certain outputs from certain inputs:

In conclusion, you learned everything a CEO Needs To Know About Machine Learning. In other words, If you need help along the way, drop us a line. We’re always happy to hear about exciting challenges: 
If you want to get more familiar how our ML process look download our Guide “How to transform data into Profit” on the kageera.com/

MLS 002: Everything a CEO needs to know about Machine Learning with Nikola Basta and Manja Bogicevic

Spartans is a global innovation powerhouse with a focus on Artificial Intelligence and
Augmented Reality. The company collaborating with leading brands around the world and helps
them integrate cutting edge technologies with emphasize on ROI. With an HQ in Tel-Aviv, Israel, and operations in Belgrade, Kyiv and New York. Our team consists of top of the line experts with
former experience in technological entrepreneurship.
https://www.spartans.tech/

MLS 003 The future and presence of Machine learning with Petar Nedeljkovic

Today we will discuss different machine learning use cases of blockchain 

Soon geat ready for our first book Everything a CEO needs to know about Machine Learning

MLS004:Machine learning use cases of Blockchain with Nikola Basta and Manya Bogicevic

In our episode 5, we had the pleasure to talk with Dimitar Dilov Chief Risk Officer at Raiffeisen Bank Serbia about machine learning in fintech and the overall future of machine learning.

MLS005 with Dimitar Dilov Machine Learning in Banks

In the MLS006 we had a pleasure to talk with Nikola Zivkovic. 


• Can you tell us more about your E-book *add question here?

To continue on the previous question. Back when I started learning ML, I was younger and more arrogant, and decided that I would learn everything about the topic in about a month. Just one more framework, how hard can it be, right? However, as it turned out, this was not just another language or programming principle. In fact, my knowledge of Object Oriented principles and functional programming was not enough to learn and understand everything coming my way. One of the things I had to do is to brush off the dust off old university books and re-utilize my knowledge of Math and Statistics. Apart from that, I had to learn a new programming language which was more suitable for this field. My main expertise back then were C# and JS, so I picked Python as my weapon of choice, as it had similarities with the languages I was comfortable with. To sum it up, I had to fight multiple battles simultaneously just to start. 
Cool thing is that during this process I took notes, writing down my struggles and that is how my personal Deep Learning journal was created and, eventually, Deep Learning for Programmers book. In this book, I’ve tried to explain the most important topics for deep learning and data science in general, but using software development perspective. Some of the concepts are implemented using Object Oriented approach just so the people with such background can have a deeper understanding of the mentioned concepts. This was a practice I personally have found to be extremely useful. Apart from that, I focused on major mathematical and data analysis topics that should be understood if you aim to do this for a living. Since in the past couple of years, Python became leading data science programming language, or leading programming language in general in this book you will learn how to use this language and use it for the data science purposes. Of course, practical examples and some of the most popular datasets were used to cover various architectures of neural networks.

• How can our listeners contact you / follow you / find you?

The best way to follow me and my interests is of course through the rubikscode.net blog or on LinkedIn and Twitter. If you want to reach me, you can send me a mail at nzivkovic@rubikscode.net or send me a direct message on mentioned social media profiles.


• Final question: Your favourite ONE book/life saving tip that can help our listeners become better Data Scientists/Machine learning Engineer/Software Developer/ Analysts?


Deep Learning for programmers by Nikola Živković :) Just kidding. Well, I am going to go completely off topic here. Being good Data Scientist/ML Engineer/Software developer is just part of the gig. I think that the ultimate goal is to become better human beings and that will in turn make you better professional as well. So, I am going to suggest Meditations by Marcus Aurelius. That is my all time favorite book, I read it almost every morning and it helped me in all of my areas of life.


Linkedin: https://www.linkedin.com/in/nmzivkovic/

Book: Deep Learning for Developers https://rubikscode.net/product/deep-learning-for-programmers-2/?wpam_id=1