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Any Machine learning engineers here ?


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Posted
14 minutes ago, csrcsr said:

Just for math yaa should be fine anna, nenubcheyaledu but based on talking to people linear algebra, little stats prob should do 

@csrcsr anna.. are you planning to switch stream or sticking with java/cloud

Posted
11 hours ago, csrcsr said:

Confused anna ml fundamentals tho deep ga nedchukine telvi ledu , currently ammavasya punnami ki  idi tippituna , old grokking kana indulo base concepts review chesadu 

https://www.educative.io/courses/grokking-modern-system-design-interview-for-engineers-managers

Same here , but going to start soon with math. Let’s see . 
 

Salary saripovatledu, yedo okati cheyyali. 

Posted
13 minutes ago, yemdoing said:

Same here , but going to start soon with math. Let’s see . 
 

Salary saripovatledu, yedo okati cheyyali. 

Anna one advice just salary aspect (adi important agree) but going into fundas of data science is long journey lot of commitment too its a dry subject 

For example maa dwgara unna tuppas structured data meeda models kosam phd ni hire chesukuntaru , imagine the compettion

One thing you can do Once you get hold of basics paina chepinatlu may be data lake side or ml ops ala try cheyochu emo good luck but any body should onow the ml ai basics you are on correct path 

Posted
5 minutes ago, csrcsr said:

Anna one advice just salary aspect (adi important agree) but going into fundas of data science is long journey lot of commitment too its a dry subject 

For example maa dwgara unna tuppas structured data meeda models kosam phd ni hire chesukuntaru , imagine the compettion

One thing you can do Once you get hold of basics paina chepinatlu may be data lake side or ml ops ala try cheyochu emo good luck but any body should onow the ml ai basics you are on correct path 

Difference between ML and MLOps ??

Posted
Just now, yemdoing said:

Difference between ML and MLOps ??

Scientist model algorithm etc

Mlops deploy manage the models , atraining the model infra etc etc 

Posted

 did like an internal 10 week course in current job, then applied 10 months in person training in ai/ml that was offered in workplace. select kaledu. then realized it is a 2-3 year commitment with mostly no returns since i don't work in big data or anything close to ai/ml. learning more to be a better in backend engineeer to jump into a better job. 
if you are under 10 years of experience may be it is worth the effort, or if you are working on some big data spark etc at your current place then there is some value in learning. 
 

  • Confused 1
Posted
42 minutes ago, enigmatic said:

 did like an internal 10 week course in current job, then applied 10 months in person training in ai/ml that was offered in workplace. select kaledu. then realized it is a 2-3 year commitment with mostly no returns since i don't work in big data or anything close to ai/ml. learning more to be a better in backend engineeer to jump into a better job. 
if you are under 10 years of experience may be it is worth the effort, or if you are working on some big data spark etc at your current place then there is some value in learning. 
 

Why no returns ? 

Posted
14 minutes ago, yemdoing said:

Why no returns ? 

lets say i work in java/python/node with aws cloud -lambda, stepfunctions, athena,glue, kinesis etc .  
jobs with spark,apache flink, hadoop and big data ecosystem etc requirement ke kastam, mostly reject avutam since they are specifically  looking for big data experience. say i learn ai/ml etc courses or training. without any prior experience i don't think i am even getting an interview screening. even in my workplace where there is an option to internally apply kastame since i don't have the specific background. forget about advance ai/ml like computer vision etc.
 

having said that if you have an internal opportunity or chance to work on some big data or ai/ml it is definitely worth learning it. also in a better job market may be there will be opportunities to transition from backend to ai/ml in smaller firms or places where they have just started exploring them.
 
i do plan on learning  some application of generative AI - langchain etc.

Posted
17 minutes ago, enigmatic said:

lets say i work in java/python/node with aws cloud -lambda, stepfunctions, athena,glue, kinesis etc .  
jobs with spark,apache flink, hadoop and big data ecosystem etc requirement ke kastam, mostly reject avutam since they are specifically  looking for big data experience. say i learn ai/ml etc courses or training. without any prior experience i don't think i am even getting an interview screening. even in my workplace where there is an option to internally apply kastame since i don't have the specific background. forget about advance ai/ml like computer vision etc.
 

having said that if you have an internal opportunity or chance to work on some big data or ai/ml it is definitely worth learning it. also in a better job market may be there will be opportunities to transition from backend to ai/ml in smaller firms or places where they have just started exploring them.
 
i do plan on learning  some application of generative AI - langchain etc.

agreed,, but generative AI - langchain is also just a piece of sdk and calling the api if you are using a framework.. so antha burra pettey pani kadu 

  • 1 year later...

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