Gnothi
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Gnothi產品資訊
Gnothi 是什麼？
Gnothi 是一個由人工智慧驅動的期刊，為使用者提供有價值的洞見和資源。
如何使用Gnothi？
要使用 Gnothi，只需創建一個帳戶並開始瀏覽文章。人工智慧算法將分析您的閱讀偏好並為您推薦個性化的內容。
Gnothi的核心功能
Gnothi 的核心特點包括以人工智慧為驅動的推薦系統、龐大的文章收藏、書籤和組織收藏夾以及追蹤特定主題或作者能力。
Gnothi 的用例
#1
了解最新的研究和發現
#2
從各個領域的專家作者中獲取洞見
#3
獲取範圍廣泛的資源以提升自我和學習能力
#4
發現利基主題並擴展您的知識
來自 Gnothi 的常見問題解答
Gnothi 如何提供個性化推薦？
我可以保存和組織我最喜歡的文章嗎？
我可以追蹤特定的主題或作者嗎？
我可以在 Gnothi 上找到什麼樣的資源？
Gnothi 不和諧
以下是 Gnothi Discord：https://discord.gg/Bhb8qYV7E6。 如欲了解更多Discord 訊息，請點選此處(/tw/discord/bhb8qyv7e6) 。
Gnothi 支援電子郵件和客戶服務聯絡資訊和退款聯絡資訊等。
以下是客戶服務的 Gnothi 支援電子郵件：Gnothi@gnothiai.com 。
Gnothi 公司
Gnothi 公司名稱：OCDevel, LLC 。
Gnothi 登入
Gnothi登入連結：https://gnothiai.com/
Gnothi 註冊
Gnothi註冊連結：https://gnothiai.com/
Gnothi Github
Gnothi Github連結：https://github.com/lefnire/gnothi
Gnothi 評論 (0)
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分析Gnothi
Gnothi 啟動嵌入
使用網站徽章來推動社區對 Toolify 發布的支持。 它們很容易嵌入您的主頁或頁腳。
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MLG 001 Introduction
Support this show by trying a walking desk (https://ocdevel.com/blog/20240109-fitness-desk) ! Show notes: ocdevel.com/mlg/1 (https://ocdevel.com/mlg/1) . MLG teaches the fundamentals of machine learning and artificial intelligence. It covers intuition, models, math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc. • MLG (https://ocdevel.com/mlg) , Resources Guide (https://ocdevel.com/mlg/resources) • Gnothi (podcast project): website (https://gnothiai.com/) , Github (https://github.com/lefnire/gnothi) What is this podcast? • "Middle" level overview (deeper than a bird's eye view of machine learning; higher than math equations) • No math/programming experience required Who is it for • Anyone curious about machine learning fundamentals • Aspiring machine learning developers Why audio? • Supplementary content for commute/exercise/chores will help solidify your book/course-work What it's not • News and Interviews: TWiML and AI, O'Reilly Data Show, Talking machines • Misc Topics: Linear Digressions, Data Skeptic, Learning machines 101 • iTunesU issues Planned episodes • What is AI/ML: definition, comparison, history • Inspiration: automation, singularity, consciousness • ML Intuition: learning basics (infer/error/train); supervised/unsupervised/reinforcement; applications • Math overview: linear algebra, statistics, calculus • Linear models: supervised (regression, classification); unsupervised • Parts: regularization, performance evaluation, dimensionality reduction, etc • Deep models: neural networks, recurrent neural networks (RNNs), convolutional neural networks (convnets/CNNs) • Languages and Frameworks: Python vs R vs Java vs C/C++ vs MATLAB, etc; TensorFlow vs Torch vs Theano vs Spark, etc
002 Habitica's Creator Recommended Usage
How to optimally use Habitica. 1. Understand dailies vs habits. Dailies have a daily quota which must be met; habits can happen or not any number of times per day. 2. Use an off-site todo app. I recommend Workflowy. Have a daily called "todo", time 30m of tackling the off-site todos. 3. USE CUSTOM REWARDS! That's the whole point of the program: pain for gain. 4. Respect the colors. Focus on the reds; relax on the greens & blues. Try to avoid perfect days. More details and class calculator: https://ocdevel.com/blog/20210108-how-to-use-habitica New project: http://gnothiai.com/