Data Science Projects with Python A case study approach to gaining valuable insights from real data with machine learning Full Book 2022

 Data Science Projects with Python A case study approach to gaining valuable insights from real data with machine learning Full Book PDF 2022

Description:

This is the most comprehensive online course for learning Python, Data Science and Machine Learning. Join us now to learn and master these topics! 

What is in this course? 

Welcome to the most comprehensive online course to learn Data Science and Machine Learning! This MasterClass has been designed to set up what seems to be the best way to go from zero to hero for Data Science and Machine Learning with Python! This course is designed for a person who already knows a little about the Python language and is ready to immerse himself in the use of these Python skills for Data Science and Machine Learning. The typical starting salary of a data scientist can easily exceed 100,000 euros annually, and we have created this course to help guide learners towards learning a set of skills that will make them extremely interesting (and attractive!) in the world of work today. We’ll cover everything you need to know about the complete Data Science and Machine Learning tech stack (technical skills) required in the best companies in the world. Our students got jobs at McKinsey, Facebook, Amazon, Google, Apple, Asana and other big tech companies! We have structured the course based on our experience of online (and face-to-face) teaching in order to propose a clear and structured approach. This will guide you to understand not only how to use the popular libraries of Data Science and Machine Learning, but also why and when we use them. This course is a perfect balance between real-world case studies and the mathematical theory behind Machine Learning algorithms = 50% Theoretical (concepts and mathematics) - 50% Practical (Python code implementation) We will cover advanced machine learning algorithms that most other courses don’t cover! Including the latest advanced regularization methods and unsupervised learning methods, such as DBSCAN. This comprehensive course is designed to match the Bootcamps, which generally cost thousands of euros. 

It will include the following topics: 

 Programming with Python: 

 NumPy with Python Pandas comprehensive learning for data analysis Complete understanding of the Matplotlib programming library Seaborn in-depth learning for data visualizations Machine Learning with Scikit-Learn We are extremely grateful for the chance we have to be able to teach you subjects that we are passionate about, such as Data Science and Machine Learning! 

Who is this course for? Python developers beginners interested in machine learning (Machine Learning) Beginner Python developers interested in data science (Data Science) Anyone wishing to learn in depth Data Science + Machine Learning

Is data science and machine learning difficult?

Good question! With your experiences in this field, the answer for you is "yes" and "no." artificial intelligence (and by extension, machine learning), is the hardest thing to do if you are inclined to go into research and push boundaries. For such work, even a doctorate.Let you know that the science of automated media called computer science, mathematics and calculations, of course, is not enough. But then, the average person has neither the ambition nor the time for such a pursuit. At the other end is what I would call applied data science and machine learning. In other words, you use existing tools, techniques and algorithms and register to solve some real-world problems. This part requires dedication, perception and creative thinking (and knowledge of some simple mathematical concepts, which are quickly learned), but with regard to real «technical» knowledge, it is much more forgiving than what the work of a software engineer calls. In other words, it’s not a walk, but going through the reward/effort ratio, is one of the best investments in the market. Now that you’ve hardened your will to become a data scientist and machine learning engineer, let’s start exploring the best options.

Machine Learning (Google):

Few people know this, but Google has a vast, very convenient and free course on machine learning. According to the company, this is part of their commitment to advancing AI/ML technologies and keeping knowledge uncovered. The best thing about this course is that there are no prerequisites, but be prepared to spend more time exploring the concepts of statistics on your own. I mean, it’s not necessary, but if you have no experience in advanced statistics, the explanations of this course may not be enough. Another problem is that this course presents machine learning via TensorFlow, which is an ML implementation developed by Google. So, in a way, Google aims to promote its APIs for machine learning, but given the value offered by this course, I don’t see how that should be a stumbling block. If anything, TensorFlow is one of the easy ways to get into the ML and enjoys crazy popularity (for a comparison of AI frameworks, see this page). Data Science: Let’s start at the beginning: this is not a quick course where you tiptoe around the Machine Learning by writing an excerpt here or a script here. This course is a severe baptism of fire that requires hard work and significant investment in time.

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