- Spatial Transformer Network
- Temporal Convolution Networks (TCN)
- Robotic OS embedded computer-vision-on-raspberry-pi
- Low power device: benchmarking-edge-computing
- Yoshua-bengio-revered-architect-of-ai-has-some-ideas-about-what-to-build-next
- gans-vs-autoencoders-comparison-of-deep-generative-models
- Disentanglement-with-variational-autoencoder-a-review
- OCR: deep-learning-is-blowing-up-ocr-and-your-field-could-be-next
- Rectified-Adam (RAdam): new-state-of-the-art-ai-optimizer
- Introduction-to-word-embeddings
- Variational-autoencoder intro
- Detecting-breast-cancer-in-histopathological-images-using-deep-learning
- Effective-data-preprocessing-and-feature-engineering
- Applications-of-reinforcement-learning-in-real-world
- Diving-deeper-into-reinforcement-learning-with-q-learning
- Cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning
- Demystifying-neural-networks-a-mathematical-approach
- Nice CNN tutorial with tensorflow
- Intuitively-understanding-convolutions-for-deep-learning
- Introduction-to-high-dimensional-hyper-parameter-tuning
- *Synthetic-data-generation
- How-to-know-when-its-time-to-show-people-your-creative-work
- *End-to-end-guide-for-machine-learning-project
- Dive-head-first-into-advanced-GANs-exploring-self-attention-and-spectral-norm
- Neural-networks for newbies
- Deep-dive-into-deep-networks-math
- Logging-in-tensorboard-with-pytorch-or-any-other-library
- Three-popular-clustering-methods-and-when-to-use-each
- Python-libraries-for-data-science-other-than-pandas-and-numpy
- Gym: reinforcement learning algorithms.
- Dash: gui-toolkit eg, dropdown list, etc
- Ipyvolume: 3D visualization
- Ipyflux: time series algorithm
- Fuzzywuzzy: string operation
- Flashtext: regular experssion and word searching
- Imbalanced-learn: learning model from imbalanced data
- Pendulum: date time processing
- 25-best-artificial-intelligence-blogs-to-follow-in-2020
- AI is-the-cause-of-and-solution-to-the-end-of-the-world
- Date-your-complement-not-your-opposite
- Does-marriage-even-make-sense-anymore
- Sleep helps better handling negative emotions
- This research suggests that sleep helps with both crystallising emotional information – and with controlling how it makes us feel. And this effect works quickly.
- Why-learning-more-isnt-always-better
- Why-procrastinators-procrastinate
- The-four-pillars-of-a-fulfilling-career
- Redundant-words-to-delete-from-your-writing
- How to predict a good data scientist
- Aristotles-timeless-advice-on-what-real-friendship-is
- Google's-AutoML will change how businesses use machine learning
- Karpathy/software-2-0
- Artificial intelligence hits the barrier of meaning
- “People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.- The Master Algorithm by Pedro Domingos”
- How to develop a healthier relationship to technology
- Understanding the media: McLuhan's famous book reference
- "A good way to evaluate utility is to see if a thing seamlessly and fluidly interacts with your body to give you more control over your surroundings, rather than them controlling you."
- George-orwells-six-rules-for-great-writing
- Summa-theologiae-by-thomas-aquinas
- Value-of-history
- The-expert-generalist: why-the-future-belongs-to-polymaths
- Watching-tv vs Reading-a-book
- Six minutes of reading can reduce stress levels by 68 percent, according to researchers at the University of Sussex. (listening to music 61 percent, drinking tea or coffee 54 percent, and taking a walk 42 percent
- Caveat of speed-reading
- I-read-one-book-100-times-over-10-years
- Marcus-aurelius-how-to-live-without-fear
- Donald Knuth: the-yoda-of-silicon-valley
- Sprezzatura: the art of making difficult things look easy
- Sex robots
- The-myth-of-mad-genius: Van Gogh, Sylvia Plath, Virginia Woolf ...
- Finishing what you started :(
- Chinese-facial-recognition-will-take-over-the-world-in-2019 (SenseTime)
- How-to-manage-your-fear-of-public-speaking
- Artificial-intelligence-salaries-heading-skyward
- Some things cannot be taught. Working with artificial intelligence does not mean you get to offload the work on the computer. It requires analytical thought process, foresight about technological innovations, technical skills to design, the skill to maintain and repair technology and software programs as well as algorithms. Therefore, it is easy to see why skilled people are so rare — which will drive AI salaries only higher.
- how-wasting-time-at-work-properly-increases-productivity
- break between works increases productivity
- take break every 90 mins (I take evrery 2-3 hours)
- break should be exploited by using some related to work (reading technical article, learning something new, thinking about the problem from a different perspective etc)
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