Data Science Books for Experienced Professionals

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Learn deep learning techniques like feedforward networks, convolutional networks, & recurrent neural nets. It covers mathematical foundations & practical methodologies used in industry.

1. Deep Learning

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2. Practical Statistics for Data Scientists

Master exploratory data analysis, experimental design, classification, and regression. This book is packed with examples to apply statistical concepts in data science.

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Dive into the theoretical foundations & mathematical derivations of ML algorithms. This book equips you with the knowledge to implement ML algorithms on your own.

3. Understanding Machine Learning

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Learn how to manipulate, analyze, & visualize data using Python with pandas, NumPy, IPython, & Jupyter. A practical introduction to data science tools for Python programmers.

4. Python For Data Analysis

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Strengthen your math background for data science, deep learning, and machine learning. This book also explores ML frameworks like TensorFlow & Keras.

5. Essential Math for Data Science

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Master the art of data visualization and communication with practical examples. Learn to create compelling data narratives for business insights.

6. Storytelling with Data

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7. Hands-On Machine Learning with Scikit-Learn and TensorFlow

Gain practical knowledge of ML algorithms, from basic regression to deep neural networks. This book is designed to help you apply ML in real-world projects.

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Explore the blog by InterviewBit for a curated list of data science books that cater to both beginners & experienced professionals. Don’t miss out on this opportunity.

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