water @wateriscoding Twitter profile

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water

2 months

Finally wrote a blog mentioning some of my resources... They are not much but i'll keep updating it (maybe). Also, my first blog so suggestions are welcome...

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@Jav_Tobrut

@sepix1215

water

@wateriscoding

5 months

be like him > make an entire os in rust > live stream the process for 2 hours daily while teaching > do not care about views and subs ABSOLUTE CHAD!!!

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@wateriscoding

4 months

thank god, 3b1b exists 🛐

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water

@wateriscoding

4 months

numpy, pandas, matplotlib

Shayan

@ImSh4yy

4 months

Postgres, Redis, S3. Name a better trio. I'll wait.

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@wateriscoding

2 months

You know the knowledge is gonna be insane when the ui looks like this

luffy

@0xluffyb

2 months

gotta love these kind of reads

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@wateriscoding

2 months

I saw this thing 5 times completely to understand it

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@wateriscoding

18 days

Anyone with this vscode theme is my enemy without introduction

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@wateriscoding

4 months

this is how i wanna learn computer architecture

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@wateriscoding

2 months

guys i am too tempted to do this... should i do this!?

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@wateriscoding

2 months

with this i successfully completed learning ml for 100 days and documented it here. i started from basics and on the 100th day trained by first transformer decoder model. i got to meet a lot of great people here on X. i am excited about the things im working on.

water

@wateriscoding

2 months

Day 100 of ML: > Finally completed the training of my gpt (decoder) model. It's a tiny language model trained on the screenplay of Titanic movie with 167k parameters. The results are not too good but they're are fine. > Finally looked a bit into llm fine-tuning and stuff Cya;)

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@wateriscoding

2 months

you're definitely missing a lot if you haven't seen it...

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@wateriscoding

18 days

Mohit Mishra

@chessMan786

18 days

Found one more cracked person. Just go for it, you will love his content

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@wateriscoding

3 months

almost completed the karpathy's nn zero to hero series (except for the gpt part, i'll start it now). there was so much to learn, i think i'll come back to it time to time to learn more

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@wateriscoding

5 months

Day 36 of ML: > almost 10.5 hours into pytorch and learnt about making classification models > Learnt about 'Sequential'. Had a lot of doubts around how to add activations across each layer but got them > No cpp today :( > also stumbled upon a great video by Samson Zhang! Cya;)

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@wateriscoding

3 months

a good video to get intro for fastapi and docker...

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@wateriscoding

1 month

> gets an unique idea no has built yet > tell friends to build it together > sees someone releasing the same idea with better features in the evening > *sobs again*

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@wateriscoding

4 months

AGI achieved!

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@wateriscoding

4 months

My GitHub is so slop man! i need to build great things. I need to get CRACKED!!!

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@wateriscoding

4 months

expect a ton of ai web apps in coming days

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@wateriscoding

3 months

Day 85 of ML: > Started learning about Transformers (attention) from karpathy lecture, got a lot of info but I'm still confused about shapes and all (i think i need to watch things again), also can you share some beginner friendly resources ;) Cya!)

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water

@wateriscoding

3 months

nice video to quickly understand saving files on aws s3

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@wateriscoding

4 months

Bro what in heaven is this!? 😭😭

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@wateriscoding

4 months

Day 64 of ML: > added activation functions (sigmoid, relu, tanh) in the go autograd (suggest a good name for this) > created backward function to backpropagate through all nodes (layers, mlp left) > ended the day with studying about constant pointers and pointers with const Cya;)

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@wateriscoding

18 days

Can someone suggest some good resources for DSA (asking for a friend obv)

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@wateriscoding

5 months

guys we eating backpropagation in deep today!!

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@wateriscoding

4 months

well well well

fabian

@fabianstelzer

4 months

just built a fully automated Wojak meme generator in Glif in 5 min: Claude 3.5 block generates the meme as JSON ComfyUI block uses a Wojak Lora to generate a fitting image JSON extractor + Canvas Block ties it all together input "AI entrepreneur" 💀

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@wateriscoding

4 months

Day 65 of ML: > added a whole neuron func and some other minor functions to the model, also half of layer done > improved the file structure and created it's packages (i had no idea about packages (skill issue)) > secured an internship > ended the day doing internship task Cya;)

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@wateriscoding

5 months

No hold up wait !?!?

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@wateriscoding

3 months

real engineers apply algorithms however they want !!!

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@wateriscoding

4 months

Imagine making a model for hours, putting all the hard work, breaking your back, straining your eyes and learning all the concepts you implement you learn along the way, just for it to give you an accuracy of 50%

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@wateriscoding

5 months

Day 33 of ML: > Decided to learn pytorch in detail and found this video > learnt everything about tensors and various functions for mat mul and others (can't build stuff due to bad internet + compute issue) > Finally ended the day with regular CPP. Cya ;)

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@wateriscoding

5 months

Day 39 of ML: > crushed the LA exam today in college > almost ~15 hours into the pytorch course and got introduced to computer vision > solved my first kaggle competition in pytorch and got a decent score Homie got seriously ill so took him to the doc (ended grind early) Cya :)

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@wateriscoding

5 months

Day 31 of ML: > made a neural network from scratch > took part in a kaggle competition and submitted the code > did CPP to end the day Will improve the competition model tomorrow I'm at home so I'm slacking off a little... Cya!

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@wateriscoding

5 months

Day 34 of ML: > 6 hours into the pytorch course and learnt the fundamentals of tensors > learnt about loss and optimisers > Made my first model with class (all the models i made so far were from scratch, as taught in f. ai course), adding train loop tomorrow Cya;)

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@wateriscoding

2 months

Day 100 of ML: > Finally completed the training of my gpt (decoder) model. It's a tiny language model trained on the screenplay of Titanic movie with 167k parameters. The results are not too good but they're are fine. > Finally looked a bit into llm fine-tuning and stuff Cya;)

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@wateriscoding

5 months

Day 37 of ML: > completed ~14 hours of the pytorch course and learnt about non linear layers and use of their functions > learnt about multi class classification models and the various activation functions to use (softmax, sigmoid, etc) > Will take part in competition tom Cya:)

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water

@wateriscoding

4 months

what do i do now chat!?

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@wateriscoding

24 days

this is great + every programmer should see the prerequisites of this course (these topics are wonderfully explained!)

Tetsuo

@7etsuo

25 days

🧵1/2 ECS 150: Operating Systems and System Programming: Prof. Porquet-Lupine, UC Davis Covers process management, synchronization, storage, virtual memory & more. Full lecture material, videos, and slides. 👇Link in comments.

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@wateriscoding

5 months

Day 38 of ML: > did a lot of linear algebra today, since I have an exam on the same tomorrow (good for ml) > made MNIST model on kaggle for the competition (needs some improvements, tomm) > no pytorch today, but will do it tom also came across this great vid, check it out Cya :)

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@wateriscoding

5 months

Day 42 of ML: > have a computer networks exams tomorrow so I studied for it for almost the entire day > finally completed ~17.25 hours of pytorch course video > learnt about creating non linear layers for simple cnn models Will compensate for the lack of ML tomorrow💪🏻 Cya:)

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water

@wateriscoding

4 months

if nothing ever works out for me, I just wanna be like him. Just Coding and having fun in my life. High in my own way!!!

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@wateriscoding

3 months

learning some flask today...

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@wateriscoding

5 months

Day 44 of ML: > Implemented backpropapation from scratch in python, took a lot of time + notes (pen+paper), but it was all worth it(karpathy sensei is a god fr) > will implement the rest of the layer and mlp tomorrow > was thinking of implementing it in CPP, should i do it? Cya;)

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@wateriscoding

3 months

wtf! i'm confused now! fastapi or flask!?

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@wateriscoding

3 months

Day 88 of ML: > Mostly caught up with work (working with models, APIs etc.) > Learnt more about RNN (seq2seq, nonseq2seq concepts) > Also a little info on attention (found this great vid. Do watch) Cya;)

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@wateriscoding

5 months

Day 43 of ML: > started implementing and making my own cnn model on FashionMNIST dataset. > Tagged along with @Kshitijjkapoor to learn and implement backpropapation from scratch this weekend > expect a backprop/gradient descent repo in my gh soon;) Cya ;)

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@wateriscoding

4 months

added the neuron as well to calculate a single result

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@wateriscoding

3 months

> i plan to buy a phone > yt shows all the good videos about the phone > i order the phone > yt starts recommending bad reviews of the phone happens everytime

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@wateriscoding

4 months

Day 53 of ML: > finally managed to bring the model to train by creating dataloaders of the dataset and then training over them (~72%) > Have to tune the hyperparameters > learnt about dataloaders, batches, etc. Actually, learnt a lot about these things in the last few days. Cya;)

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@wateriscoding

4 months

Day 63 of ML: > started making neural networks from scratch in go and made the basic methods and backward methods in it > I'm aware that i was making makemore mlp and I'll be continuing it (have something in mind) > realised my struggle in pointers and started learning them Cya;)

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@wateriscoding

4 months

Saw this kid teaching DSA on yt while i haven't even started it yet

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@wateriscoding

4 months

Day 51 of ML: > Learning about fine-tuning models through the playbook and applying it > Learning about Transformers and how to train models using int and text data for a project (any resources for them are welcome) Cya;)

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@wateriscoding

4 months

here are some serious reasons gang

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@wateriscoding

3 months

Guys, just started learning about deep learning. When does this Transformers and diffusion come guys!?

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@wateriscoding

4 months

since you guys trashed me for doing matrix multiplication the hard way, here is another way-

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@wateriscoding

2 months

Day 99 of ML: > Worked some more on improving apis and models > Implemented multi head and blocks to the transformer but this model won't train due to low gpu 😭, I'll try to train it again on cloud gpu tmrw (Btw here's the code ->) Cya;)

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@wateriscoding

6 months

Hello my 7 followers, let's crush it today!

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@wateriscoding

2 months

New dopamine hit just dropped!

maharshi

@mrsiipa

2 months

ik what i'm watching tonight.

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@wateriscoding

5 months

Day 40 of ML: > Got ~16 hours into the pytorch course and now learning computer vision basics > learnt about dataloaders, flatten layer and other layers in the model. > couldn't do much since exams are ongoing and had to study for tomorrow, will compensate it tomorrow ;) Cya :)

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@wateriscoding

4 months

added relu, sigmoid and tanh functions in the autograd in go. now going to attempt amazon ml school exam without studying anything. let's see how it goes...

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@wateriscoding

3 months

i love my feed when everyone is posting their W's, posting code snippets and trying out new things. honestly, it inspires me to do more things

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@wateriscoding

4 months

also implemented the layer of the Network...

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@wateriscoding

5 months

thank you so much gods of ml for creating pytorch

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@wateriscoding

3 months

Day 86 of ML: > Worked a lot on api and finally solved a major bug bugging me (now it shouldn't take much long to finish) > Also continued learning about Transformers, learnt a little about RNNs (FAFO) and found a great lecture around it, will continue more of it Cya;)

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@wateriscoding

14 days

The main problem with new programmers like me is learning higher level programming and completely ignoring the underlying processes that run in the background and run the entire thing

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@wateriscoding

5 months

Day 41 of ML: > Watched cs231n's backprop lecture to understand backprop basics in depth, i might make it from scratch > ~16.5 hours into the pytorch course and learnt to make dataloaders, training and testing loops functions and other things > will revise cnn before sleep Cya:)

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@wateriscoding

5 months

Day 35 of ML: > ~8.5 hours into the course and i completed the second part, learnt about losses, optimisers and other stuff > tried building my own model on my laptop, had to cut down 1.1 million rows down to 10k rows (CPU issue) > Finally some CPP to end the day Cya ;)

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water

@wateriscoding

4 months

@0xluffyb i've been willing to do something like this since long... haha

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@wateriscoding

3 months

Can't understand the uni professor's hate for LLMs. Not allowing to use it while it is the best tool to learn things

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@wateriscoding

3 months

ML update: > Guys due to a very tragic unfortunate event I wasn't able to study ml today and probably won't do it for a few more days.

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@wateriscoding

5 months

Day 46 of ML: > Participated in the kaggle competition and made the model myself, used the wrong optimizer 🤦🏻 but then changed it and the results improved (took a lot of time), will improve it more tomorrow > also completed the implementation part of neuron, layers and mlp Cya;)

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@wateriscoding

4 months

man i hate data preprocessing so much

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@wateriscoding

26 days

Final year project team members selection is where the friendships break

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@wateriscoding

3 months

I think no one has had a greater influence over the ml community as karpathy sensei. I mean it's because of him that people are able to think about making LLMs not just in python but in other languages. I don't know if I'll be able to meet him in this life but i owe him a lot.

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@wateriscoding

5 months

Learnt a little about computer vision and CNNs and my mind is already full of ideas

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@wateriscoding

4 months

Day 71 of ML: > completed and implemented the mlp part of wordmore in python (enjoyed it, left with go but guys build multidimensional things first) > started with activations, gradients and batch norm part of wordmore (the rnn architecture) Will complete it soon too!!! Cya;)

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@wateriscoding

5 months

Great read! Guys give it a try 👇🏻

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@wateriscoding

5 months

Guys joining reddit AGAIN. Please suggest some good subreddits for ai/ml/dl stuff obviously

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@wateriscoding

5 months

Day 45 of ML: > completed the neuron, layers and mlp part of the nn video, i will implement it in code tomorrow > Got the TOC exam tomorrow so spent most of the day studying for it > Will do more tomorrow Cya;)

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@wateriscoding

3 months

Day 75 of ML: > Rebuilt the entire transformer model i made a few days ago to find shortcomings and improve it (took the entire day but it was worth it + i understood most of the code this time) > advanced on my way to become a backprop ninja (this is really helping me out) Cya;)

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@wateriscoding

4 months

@notyamisukehiro he kinda looks like kanye west

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@wateriscoding

4 months

guys i need discipline😭😭

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@wateriscoding

2 months

Bro calls himself a programmer but couldn't install the compiler on the lab pc 😭

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@wateriscoding

5 months

Day 32 of ML: > spent half of the day figuring about hidden layers and neurons until i made it from scratch. > added the layer to the model but the laptop memory ran out > Eureka moment when I saw how to make nn with classes in pytorch > Finally some CPP to end the day Cya ;)

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@wateriscoding

5 months

Guys after completing fastai part 1, i don't think I'm still ready for part 2 (the diffusion thing looks tough), what would you suggest I do now?

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@wateriscoding

4 months

I f****ing hate my college fr. Lost another previous opportunity thanks to them.

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@wateriscoding

4 months

Day 66 of ML: > Added layers, MLP and other minor functions to this autograd project > Implemented the first karpathy vid on nn in golang (the project is complete till there) > did a lot of data processing and model searching research for internship tasks > Ended with rest Cya;)

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@wateriscoding

3 months

Visualization is the key to understand anything

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@wateriscoding

4 months

Day 67 of ML: > added Matrix multiplication and other minor functions in the go autograd (thinking of taking it multidimensional) > Revised makemore model (also planning to make it in go) > Did a lot of model training, tuning and debugging for work model Cya;)

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@wateriscoding

1 month

Wanna get cracked at low level programming... Then i see stuff like this

Mustafa

@mustafa_kh4n

1 month

CNN architecture in plain C.

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@wateriscoding

4 months

today i'm making this...

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@wateriscoding

3 months

So we getting good frontend in python as well!?

Jeremy Howard

@jeremyphoward

3 months

Announcing FastHTML. A new way to create modern interactive web apps. Scales down to a 6-line python file; scales up to complex production apps. Auth, DBs, caching, styling, etc built-in & replaceable and extensible. 1-click deploy to @Railway , @vercel , @huggingface , & more.

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@wateriscoding

5 months

"Why isn't it possible ?" ""Why not!?

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@wateriscoding

1 month

everywhere i go and see, i am asked about certification... and i have nothing to put... i have learnt everything from youtube and other sources...

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@wateriscoding

4 months

Day 72 of ML: > Learnt about activations, initialising the gradients, and a lot about batch norms (sensei is a god for existing these things so simply) > did some research and results comparisons of models > will apply all the learnt things tomorrow Cya;)