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alxndrTL/little-book-rl

The Little Book of Reinforcement Learning

#Learning resources
Visit GitHub
Python
1.7k
97
1 contributors
AchievementsView all →
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Momentum

How fast alxndrTL/little-book-rl is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Aug 27 – Oct 25, 2026

Stars +172 in 60 days

0102030
30

Forks +19 in 60 days

0123
3

Merged PRs 0 in 60 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Aug 27Sep 4Sep 12Sep 20Sep 28Oct 6Oct 14Oct 22
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Thu, Aug 27, 2026+5+00
Fri, Aug 28, 2026+5+10
Sat, Aug 29, 2026+1+00
Sun, Aug 30, 2026+1+00
Mon, Aug 31, 2026+1+00
Tue, Sep 1, 2026+1+00
Wed, Sep 2, 2026+2+00
Thu, Sep 3, 2026+5+10
Fri, Sep 4, 2026+1+00
Sat, Sep 5, 2026+2+00
Sun, Sep 6, 2026+3+10
Mon, Sep 7, 2026+3+10
Tue, Sep 8, 2026+3+10
Wed, Sep 9, 2026+1+00
Thu, Sep 10, 2026+1+00
Fri, Sep 11, 2026+3+00
Sat, Sep 12, 2026+2+00
Sun, Sep 13, 2026+0+00
Mon, Sep 14, 2026+2+10
Tue, Sep 15, 2026+1+00
Wed, Sep 16, 2026+3+00
Thu, Sep 17, 2026+3+20
Fri, Sep 18, 2026+3+00
Sat, Sep 19, 2026+1+00
Sun, Sep 20, 2026+4+00
Mon, Sep 21, 2026+2+00
Tue, Sep 22, 2026+0+00
Wed, Sep 23, 2026+2+00
Thu, Sep 24, 2026+0+20
Fri, Sep 25, 2026+5+00
Sat, Sep 26, 2026+30+30
Sun, Sep 27, 2026+6+20
Mon, Sep 28, 2026+4+10
Tue, Sep 29, 2026+4+00
Wed, Sep 30, 2026+2+00
Thu, Oct 1, 2026+2+10
Fri, Oct 2, 2026+1+00
Sat, Oct 3, 2026+1+00
Sun, Oct 4, 2026+5+00
Mon, Oct 5, 2026+2+00
Tue, Oct 6, 2026+3+00
Wed, Oct 7, 2026+2+00
Thu, Oct 8, 2026+2+00
Fri, Oct 9, 2026+3+00
Sat, Oct 10, 2026+1+00
Sun, Oct 11, 2026+1+00
Mon, Oct 12, 2026+3+00
Tue, Oct 13, 2026+2+00
Wed, Oct 14, 2026+10+20
Thu, Oct 15, 2026+11+00
Fri, Oct 16, 2026+2+00
Sat, Oct 17, 2026+1+00
Sun, Oct 18, 2026+1+00
Mon, Oct 19, 2026+0+00
Tue, Oct 20, 2026+1+00
Wed, Oct 21, 2026+2+00
Thu, Oct 22, 2026+2+00
Fri, Oct 23, 2026+0+00
Sat, Oct 24, 2026+2+00
Sun, Oct 25, 2026+0+00
Total+172+190
  • 1#1 on the list
  • 7Rank that day
  • Not trending
  • Mentions and achievements

    Where people are talking about alxndrTL/little-book-rl, and every badge it has earned
    1. Oct 141 post
      • 有个里尔的在校学生,一个人写了本强化学习小书,little-book-rl,GitHub 1600 多 star。 从基础概念讲到 PPO,每个算法配了能跑的 PyTorch 代码,动态规划那部分带完整推导。书免费看,纸质版亚马逊也有。 我翻了下目录,比一上来甩公式的教材友好。想入门 RL 又不知道从哪下手的,从这本开始。

        Read full on X, posted by @Richardomuhuai

        @Richardomuhuai · x.com

    2. 19 days earlier
    3. Sep 251 post
      • 想入门强化学习,论文啃不动,博客又零散,系统还不太劝退的资料难道好找? 《The Little Book of Reinforcement Learning》这本开源书,页数不多,从基础概念一路铺到常用算法。 PyTorch 代码全套附上,书里每个算法都有能跑的实现,读一段练一段。 GitHub: 另外还配了一份动态规划的详细推导,想抠数学细节的可以对着翻。…

        Read full on X, posted by @Gas1688

        @Gas1688 · x.com

    4. 2 months earlier
    5. Aug 51 post
      • 想学强化学习,看论文太硬核,看博客又太碎片,找一份系统又不劝退的入门资料不容易。 《The Little Book of Reinforcement Learning》这本开源书籍,篇幅不长,从基础概念讲到常用算法。 附带全套 PyTorch 代码,书里讲到的每个算法都有可运行的实现,边读边练。 GitHub: 还有一份动态规划的详细推导作为补充,想深入数学细节的可以对照看。…

        Read full on X, posted by @GitHub_Daily

        @GitHub_Daily · x.com

    6. 16 days earlier
    7. Jul 201 post
      • found the little book of reinforcement learning! from what I see, seems like a beautiful little resource to learn the in's and out's of RL, in little over a hundred pages! it's free on github!

        Read full on X, posted by @RuiCarrilho5

        @RuiCarrilho5 · x.com

    8. Jul 171 post2 posts
      • The Little Book of Reinforcement Learning

        Read full on Reddit

        r/hackernews

      • CD sales growth outpaced vinyl in the first half of 2026 (

        Read full on X, posted by @betterhn50

        @betterhn50 · x.com

    9. Jul 162 posts
      • The Little Book of Reinforcement Learning

        Read full on Reddit

        r/hypeurls

      • The Little Book of Reinforcement Learning

        Read full on Hacker News

        Hacker News

    10. Jul 121 post
      • +30 pages to cover to successful applications of RL : RLVR/LLM and AlphaGo Zero. Great to understand the challenges related to RL at scale, like why GRPO, policy staleness etc

        Read full on X, posted by @AlexandreTL2

        @AlexandreTL2 · x.com

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