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Are you looking to get started with Python and Machine Learning?
Look no further! This comprehensive 2-in-1 bundle is the perfect resource for beginners looking to learn both Python and Machine Learning in one easy guide.
With this book, you'll be able to grasp the basic fundamentals of Python and learn how to use it to solve real-world problems. You'll also get a crash course in Machine Learning, including key concepts, algorithms, and techniques.
In the Chapter 3, we will look at some of the useful techniques for efficiently loading, storing and manipulating in-memory data in Python. The topic is vast because the sources from which data can be extracted are vast it includes document collection, image collection, sound clips collection, or any other thing. Although, on the façade, the data is heterogenous, it will be taken fundamentally as arrays of numbers. Let us take a quick example of digital images. They can be simply taken as two-dimensional arrays of numbers which denote pixel brightness across the area. Moreover, Sound clips can be taken as one-dimensional arrays of intensity vs time. Time, likewise, can be transformed into numerical representations in numerous ways (One way is binary digits signifying the frequency of some pair of words or words only).
Owing to this cause, good storage and manipulation of numerical arrays is the core of every process in Data Science. Now, there are two specialized tools that Python uses for handling these numerical arrays: the NumPy package, and the Pandas package. In this chapter we will go into the details of the NumPy package. NumPy is the compact form for Numerical Python. It gives an effective interface to work on heavy data buffers. You may take NumPy as Python’s ready-made list type, but its storage and data operation capabilities are much sounder, especially when the arrays become larger in size.
Whether you're new to programming or looking to improve your Machine Learning knowledge, this bundle has it all. You'll be able to educate yourself on the current and emerging technologies of the future, all in one convenient resource. So don't wait - start your journey to becoming a Python and Machine Learning expert today!
CHAPTER 1 The BEGINNING OF DATA SCIENCE
CHAPTER 2 INTRODUCTION TO MACHINE LEARNING
CHAPTER 3 INTRODUCTION TO NUMPY
Aggregations: Min, Max, and Everything In Between
CHAPTER 4 INTRODUCTIONS TO VISUALIZATIONS WITH MATPLOTLIB
CHAPTER 5 INTRODUCTION TO DATA CLEANING AND MANIPULATIONS WITH PANDAS
CHAPTER 6 SQL AND DATABASE QUESTIONS AND PREP
CHAPTER 7 STATISTICS AND PROBABILITY
CHAPTER 8 PREDICTIVE MODELING AND MACHINE LEARNING QUESTIONS
PREDICTIVE MODELING INTERVIEW QUESTIONS
Machine Learning Interview Questions