Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile
Solid Green Fire 木熒

@solidgreenfire

Wisdom-based Data editor (Chinese and English). Generalist, Empath, Flâneur. Creating training dataset with Dark data.

ID: 1172898402352295941

linkhttps://medium.com/@snllab/ calendar_today14-09-2019 15:43:59

4,4K Tweet

83 Takipçi

318 Takip Edilen

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 299: We connect the fragments and interactions, cross the boundaries, and integrate all angles to discover all the points, lines, planes, and volumes. Dark data eventually show up.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 300: Practicing real listening are like we seeking ways to trace a river back to its source, in order to uncover the meaning and emotions behind the message, as well as the effects it will trigger.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 301: Premium data is like water from its source. The closer it is to the heart’s true message, the clearer it becomes.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 302: The real issue is understanding what premium data is as understanding what what pure water looks like. We need to learn to filter out impurities and remaining unaffected by temporary turbidity.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 303: Real listening is a psychological act that uses heartfelt awareness to perceive the other person’s expressions while reflecting on the key points in the message.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 304: Many people often confuse “self-righteousness” with “correct understanding” and keep to make the same mistakes. Noise making is kind of dark data.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 305: The Doorman fallacy reminds us that intangible value is the core competitiveness.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 306: The truth we see is not necessarily absolute facts. In the time of exploration, we need to maintain skepticism along with a certain degree of sensibility, patience, and intuition.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 307: The significance of reading lies in making some vague and unclear feelings increasingly clear. It help us understand where these feelings come from and where they are going.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 308: Tacit knowledge like creativity, aura, expression skills, association, perception etc. related to Taste are not about making things more gorgeous, dazzling, or pleasing to the eye.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 309: Closing our eyes, filtering the received information, and identify the kernel of data. This is a form of liberation that can help everyone see more broadly and farther.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 310: Plans are calculated according to static conditions and the creation of defects; interactions are calculated according to dynamic intermingling, leading to multi-faceted and homeostasis.

Solid Green Fire 木熒 (@solidgreenfire) 's Twitter Profile Photo

How we create training dataset with Dark data? Day 311: The eyes are the windows to the soul. From a person’s gaze, one can discern the contours of the soul.