In 'Pragmatic Thinking and Learning: Refactor Your Wetware', Andy Hunt explores how our brains are wired and provides practical tips to enhance learning and thinking. The book delves into cognitive science and learning theories, offering strategies to become more effective in acquiring new skills and managing knowledge.
Deep Learning Illustrated is a comprehensive guide to deep learning, offering a unique visual and interactive approach. It explains deep learning techniques through straightforward analogies, vivid illustrations, and hands-on Python code in Jupyter notebooks. The book covers essential theory, including artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), and deep reinforcement learning. It also focuses on practical applications such as machine vision, natural language processing, image generation, and game-playing algorithms, using libraries like Keras, TensorFlow, and PyTorch.
In 'Limitless,' Jim Kwik offers a comprehensive guide to upgrading brain performance. The book is divided into three main parts: Mindset, Motivation, and Methods. Kwik provides tools to challenge limiting beliefs, ignite motivation, and master methods for accelerated learning. He introduces the 'Limitless Model,' which includes the FASTER method for quick content absorption and strategies to improve focus, study habits, memory, and speed reading. The book also addresses modern-day 'supervillains' of learning, such as digital deluge, and offers practical exercises to implement these strategies immediately[2][4][6].
In 'A Mind for Numbers', Dr. Barbara Oakley provides practical advice and scientific insights on how to excel in math and science, even for those who have struggled in these subjects. The book highlights the importance of using both focused and diffuse modes of thinking, managing time effectively, and applying strategies such as interleaved practice and spaced repetition. Oakley shares her personal journey from being a mathphobe to becoming an engineering professor, illustrating that anyone can improve their skills in these areas with the right approach.
This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It focuses on the Python programming language and its data-oriented library ecosystem, particularly pandas, NumPy, and Jupyter. The book equips readers to become effective data analysts by providing a guide to the latest versions of these tools. It covers data manipulation, preparation, and cleaning, and is ideal for those looking to build data applications using Python[2][4]
In 'Mastery', Robert Greene argues that mastery is not an innate talent but a skill that can be developed through a rigorous process. The book outlines several key stages: finding your life's task, undergoing an ideal apprenticeship, finding the right mentor, acquiring social intelligence, and fusing intuitive with rational thinking. Greene draws on the lives of historical and contemporary masters such as Mozart, Einstein, and Temple Grandin to illustrate his points. He emphasizes the importance of deep practice, self-directed learning, and the ability to read and navigate social dynamics. The book challenges the conventional notion of genius as a genetic gift and offers practical steps for anyone to achieve mastery in their chosen field.
Harpreet Sahota joins us to discuss his data science mentorship work outside his day job and how you can land your dream job.
In this episode you will learn:
- Harpreet’s current life and location [2:25]
- Data Community Content Creator Awards [8:37]
- The Artists of Data Science Podcast [14:46]
- Data Science Dream Job [24:18]
- Harpreet’s day job at Price Industries [30:48]
- Coming in data science from a non-data background [40:55]
- Tools and skills to know [47:57]
Additional materials: www.superdatascience.com/457
Super Data Science: ML & AI Podcast with Jon Krohn 
