Thanks

What's ISPL?

@@datascienceinyourpocket introduction to statistical learning

Introduction to statistical learning

I would suggest a mix of both (with an inclination towards ISLP). Practical hands on is now very easy with all these readymade libraries. It can be done in a week or two

@@datascienceinyourpocket thanks mate

Glad it was helpful!

Thank you😁

Thank you☺️

Thanks 😊

Thank you😊

Thank you😁😁

It is. Checkout some posts on Mercor AI interview process. Very similar

Read this sometime back, was quite good : www.oreilly.com/library/view/think-stats-2nd/9781491907344/

Thank you🥰

Thanks for the feedback

You can follow the other videos in the playlist to under LangGraph completely

please provide the code also

please provide the code also

Thank you😁

This is getting generated using LLMs in background. I don't think there would be copyright issues

Can you paste the entire error log? Also, do checkout the value for user_proxy object (just print) before executing this line

@@datascienceinyourpocket This is the user_proxy object <autogen.agentchat.user_proxy_agent.UserProxyAgent object at 0x000002B2FC9D3490> Rest of the error log userproxy (to assistant): Write a shell script to display files -------------------------------------------------------------------------------- --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In[14], line 32 23 user_proxy = UserProxyAgent( 24 "userproxy", 25 is_termination_msg=lambda x:x.get("content","") and x.get("content","").rstrip().endswith("TERMINATE"), 26 human_input_mode="NEVER", 27 max_consecutive_auto_reply=5 28 ) 30 print(user_proxy) ---> 32 chat_result = user_proxy.initiate_chat(assistant,message="Write a shell script to display files") 33 pprint.pprint(chat_result) File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:1018, in ConversableAgent.initiate_chat(self, recipient, clear_history, silent, cache, max_turns, summary_method, summary_args, message, **kwargs) 1016 else: 1017 msg2send = self.generate_init_message(message, **kwargs) -> 1018 self.send(msg2send, recipient, silent=silent) 1019 summary = self._summarize_chat( 1020 summary_method, 1021 summary_args, 1022 recipient, 1023 cache=cache, 1024 ) 1025 for agent in [self, recipient]: File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:655, in ConversableAgent.send(self, message, recipient, request_reply, silent) 653 valid = self._append_oai_message(message, "assistant", recipient) 654 if valid: --> 655 recipient.receive(message, self, request_reply, silent) 656 else: 657 raise ValueError( 658 "Message can't be converted into a valid ChatCompletion message. Either content or function_call must be provided." 659 ) File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:818, in ConversableAgent.receive(self, message, sender, request_reply, silent) 816 if request_reply is False or request_reply is None and self.reply_at_receive[sender] is False: 817 return --> 818 reply = self.generate_reply(messages=self.chat_messages[sender], sender=sender) 819 if reply is not None: 820 self.send(reply, sender, silent=silent) File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:1974, in ConversableAgent.generate_reply(self, messages, sender, **kwargs) 1972 continue 1973 if self._match_trigger(reply_func_tuple["trigger"], sender): -> 1974 final, reply = reply_func(self, messages=messages, sender=sender, config=reply_func_tuple["config"]) 1975 if logging_enabled(): 1976 log_event( 1977 self, 1978 "reply_func_executed", (...) 1982 reply=reply, 1983 ) File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:1340, in ConversableAgent.generate_oai_reply(self, messages, sender, config) 1338 if messages is None: 1339 messages = self._oai_messages[sender] -> 1340 extracted_response = self._generate_oai_reply_from_client( 1341 client, self._oai_system_message + messages, self.client_cache 1342 ) 1343 return (False, None) if extracted_response is None else (True, extracted_response) File ~\anaconda3\lib\site-packages\autogen\agentchat\conversable_agent.py:1364, in ConversableAgent._generate_oai_reply_from_client(self, llm_client, messages, cache) 1358 # TODO: #1143 handle token limit exceeded error 1359 response = llm_client.create( 1360 context=messages[-1].pop("context", None), 1361 messages=all_messages, 1362 cache=cache, 1363 ) -> 1364 extracted_response = llm_client.extract_text_or_completion_object(response)[0] 1366 if extracted_response is None: 1367 warnings.warn(f"Extracted_response from {response} is None.", UserWarning) File ~\anaconda3\lib\site-packages\autogen\oai\client.py:914, in OpenAIWrapper.extract_text_or_completion_object(cls, response) 902 @classmethod 903 def extract_text_or_completion_object( 904 cls, response: ModelClient.ModelClientResponseProtocol 905 ) -> Union[List[str], List[ModelClient.ModelClientResponseProtocol.Choice.Message]]: 906 """Extract the text or ChatCompletion objects from a completion or chat response. 907 908 Args: (...) 912 A list of text, or a list of ChatCompletion objects if function_call/tool_calls are present. 913 """ --> 914 return response.message_retrieval_function(response) File ~\anaconda3\lib\site-packages\autogen\oai\client.py:142, in OpenAIClient.message_retrieval(self, response) 139 return [choice.text for choice in choices] # type: ignore [union-attr] 141 if TOOL_ENABLED: --> 142 return [ # type: ignore [return-value] 143 ( 144 choice.message # type: ignore [union-attr] 145 if choice.message.function_call is not None or choice.message.tool_calls is not None # type: ignore [union-attr] 146 else choice.message.content 147 ) # type: ignore [union-attr] 148 for choice in choices 149 ] 150 else: 151 return [ # type: ignore [return-value] 152 choice.message if choice.message.function_call is not None else choice.message.content # type: ignore [union-attr] 153 for choice in choices 154 ] TypeError: 'NoneType' object is not iterable

Let me check and revert on this

@@datascienceinyourpocket Looking forward to it. Thanks! ☺

Thanks

Thank you☺️

Did this way back. Need to go back and recheck

@@datascienceinyourpocket thank you for your reply. Would really appreciate if you could guide a bit

Sure, give me sometime

Thanks 😊😊