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Replace image links from postimg.org to postimg.cc #282

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Sep 5, 2019
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Replace image links from postimg.org to postimg.cc #282

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2 changes: 1 addition & 1 deletion week1_intro/primer/recap_tensorflow.ipynb
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Expand Up @@ -243,7 +243,7 @@
"\n",
"Here's what you should see:\n",
"\n",
"<img src=\"https://s12.postimg.org/a374bmffx/tensorboard.png\" width=480>\n",
"<img src=\"https://s12.postimg.cc/a374bmffx/tensorboard.png\" width=480>\n",
"\n",
"Tensorboard also allows you to draw graphs (e.g. learning curves), record images & audio ~~and play flash games~~. This is useful when monitoring learning progress and catching some training issues.\n",
"\n",
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10 changes: 5 additions & 5 deletions week4_approx/dqn_atari.ipynb
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Expand Up @@ -47,7 +47,7 @@
"metadata": {},
"source": [
"### Let's play some old videogames\n",
"![img](https://s17.postimg.org/y9xcab74f/nerd.png)\n",
"![img](https://s17.postimg.cc/y9xcab74f/nerd.png)\n",
"\n",
"This time we're gonna apply approximate q-learning to an atari game called Breakout. It's not the hardest thing out there, but it's definitely way more complex than anything we tried before.\n"
]
Expand Down Expand Up @@ -193,7 +193,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"![img](https://s17.postimg.org/ogg4xo51r/dqn_arch.png)"
"![img](https://s17.postimg.cc/ogg4xo51r/dqn_arch.png)"
]
},
{
Expand Down Expand Up @@ -311,7 +311,7 @@
"### Experience replay\n",
"For this assignment, we provide you with experience replay buffer. If you implemented experience replay buffer in last week's assignment, you can copy-paste it here __to get 2 bonus points__.\n",
"\n",
"![img](https://s17.postimg.org/ms4zvqj4v/exp_replay.png)"
"![img](https://s17.postimg.cc/ms4zvqj4v/exp_replay.png)"
]
},
{
Expand Down Expand Up @@ -409,7 +409,7 @@
"\n",
"$$ Q_{reference}(s,a) = r + \\gamma \\cdot \\max _{a'} Q_{target}(s',a') $$\n",
"\n",
"![img](https://s17.postimg.org/x3hcoi5q7/taget_net.png)\n",
"![img](https://s17.postimg.cc/x3hcoi5q7/taget_net.png)\n",
"\n"
]
},
Expand Down Expand Up @@ -673,7 +673,7 @@
"\n",
"But hey, look on the bright side of things:\n",
"\n",
"![img](https://s17.postimg.org/hy2v7r8hr/my_bot_is_training.png)"
"![img](https://s17.postimg.cc/hy2v7r8hr/my_bot_is_training.png)"
]
},
{
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4 changes: 2 additions & 2 deletions week5_policy_based/practice_a3c.ipynb
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Expand Up @@ -103,7 +103,7 @@
"Your assignment here is to build and apply a neural network - with any framework you want. \n",
"\n",
"For starters, we want you to implement this architecture:\n",
"![https://s17.postimg.org/orswlfzcv/nnet_arch.png](https://s17.postimg.org/orswlfzcv/nnet_arch.png)\n",
"![https://s17.postimg.cc/orswlfzcv/nnet_arch.png](https://s17.postimg.cc/orswlfzcv/nnet_arch.png)\n",
"\n",
"After your agent gets mean reward above 50, we encourage you to experiment with model architecture to score even better."
]
Expand Down Expand Up @@ -263,7 +263,7 @@
"metadata": {},
"source": [
"### Training on parallel games\n",
"![img](https://s7.postimg.org/4y36s2b2z/env_pool.png)\n",
"![img](https://s7.postimg.cc/4y36s2b2z/env_pool.png)\n",
"\n",
"To make actor-critic training more stable, we shall play several games in parallel. This means ya'll have to initialize several parallel gym envs, send agent's actions there and .reset() each env if it becomes terminated. To minimize learner brain damage, we've taken care of them for ya - just make sure you read it before you use it.\n"
]
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