My mistake is to aim for perfection instead of completion.. learning the same thing in multiple ways which drains so much of time ..Research thodi kr rhe hain itna time bithane ke liye... Learning --Implementation---Learning--Growing .. cycle should be like this. And my other mistake is to ignore deployment of models
Mistakes 1) False expectations 2) Not following single roadmap 3) Lack of consistency 4)ignoring pillars of data science -python, sql and statistics 5)ignoring pillars of data science-Data Preprocessing, feature engineering ,exploratory data analysis 6) Not working on real-world datasets 7) wrong order of study(ML algorithms) 8) Not focusing on deployment 9) not starting interview preparation on day 1 10) not having mentor or study group
Mistake done by me while learning DS/ML/Python: Memorizing syntax - I was thinking I should write code without using google. Even in interview no one expects correct syntax from you, all they expect from u is how much you know concept. Though you must know basic syntax to clear coding round.
1. Revising python libraries again and again. It is a high possibility that you may forget the numpy pandas operations during execution. So you just need to take overview of code from internet and eventually you will start remembering them after 8-10 datasets. 2. Consistency - For this spiral method works which sir suggested i.e first take overview of topic and then do the topic again (Its like ek ek karke dhaage kholna) 3. No friends to study and never tried to talk with random. Extra: 4. Mental Health - Jabtak dimmag shaant nahi rahega , business wala dimaag nahi chalega aur fir data science mein maza bhi nahi aega.
I have done all these mistakes and was demotivated. I will start again after watching this video. I purchased your DSMP 2.0 program. I found a good teacher now but very late.Thank you for being so honest in your teachings and making ML concepts easier for us.
1. Changed my roadmap quite a few times, which slowed my learning drastically. I think I studied same Pandas, Numpy, data viz libraries more than 2-3 times, but studied the same thing just for this mistake. 2. Inconsistency. I learnt, I stopped, and I forgot. And again the same circle!
The video was like a mirror for me . I realised I was doing the same mistakes, but still in my learning phase so I can rectify it. Thank you so much for sharing
Sir i have followed all your course and for me you are best teacher regarding data science. I want you to create a playlist on model deployment and integration into website, android app and desktop application.
All most all mistakes i have experienced from from same bhai.. and started over coming from them... any way thanks for sharing without any hesitation.... 👍
1. Set fair time period to learn 2. Stick to one Roadmap 3. Consistency 4. Masters the pillars of data science (Python, SQL, Statistics & Maths) 5. Master -> Data Preprocessing, Feature Engineering, Exploratory Data Analysis 6. Try to work on Real Life Datasets 7. Give much time learning important ML algorithms 8. Deployment and management of Model 9. Prepare for interview simultaneously after learning anything 10. Motivation by mentor/study groups
3-Pillars Python, SQL , Maths(Stats, Linear Algebra, Probability) TOP 10 Machine Learning Agorithms Linear regression Logistic regression Decision tree SVM algorithm Naive Bayes algorithm KNN algorithm K-means Random forest algorithm Dimensionality reduction algorithms Gradient boosting algorithm and AdaBoosting algorithm Comment if Order is right, As I have just copied it from google.
1 KNN 2 naive bayes 3 linear regression 4 logistic regression 5 linear SVM 6 dual form of SVM 7 gradient descent 8 decision tree 9 random forest 10 GBDT 11 ada boost 12 Xgboost 13 PCA 14 t sne
Mistakes in my DS journey 1. Focussing on implementation rather than in-depth knowldege. 2.Not getting into depth of things/ Having a superficial approach. 3. Thinking I understood it without actually understanding
I am master student in AI and all these things in my cirruculam 1. mistake I have not done learn theory that spoil time to learn practical and practice again so try both things parellel....theory and its practice
I was learning ML for about a year (to be honest I was frustrated)and I saw this video, I am committing 6 out of these 10 mistakes. Thanks to him for letting me know what I was missing. In the last part where he mentions that one should have a mentor or a study group, I totally agree with that and that someone who wants to team up is welcomed.
I think you have covered all common mistakes that anyone can do or have done in past. Apart from this, I think one can also be distracted by some other courses just by seeing their salary and scope or may lose hope by seeing any negative feedback or review about data science. So, if you have decided to become a data scientist then remain stick to the course until you got a start in this field
We r very lucky to have a mentor like u sir. Very greatful to u n ur channel. Thanku so much. I did same mistakes u told. Still learning. Now that ur channel is there , i stay motivated.
It's been almost 3 months i have started learning n practicing data science stuff trust me doing simple exploratory analysis on real world data is very difficult compare to learning ml dl models n maths
Great video....I just started learning Data Science.....This video will really help me not make these mistakes. If anybody is also like me who have just started can connect to me to form a study group.
Correctly said Bhai, inconsistent, less practice are my mistakes. Now i need to work on because I am from Non-tech background. While watching videos it looks like a cakewalk but in real it's not!!
Me bhi yhi mistake kr rha hun 6 months me data science khatm...aapka roadmap sahi he ....consistent ni hona ek ar galti ...python ,sql ,statistics strong krna ye sahi baat he ...data clean krne pe aaj se focus rahega maximum....real world data set and pe abhi tak me try ni kiya ........interview preparation wali baat sabse important .........thanks for this suggestion
heyy learners and nitish sir too i m following youtube vedio only is it sufficient to learn or DSMP 2.0 is really much more conttent please reply on it that will be greatful.
Hi sir, i am new to your channel from machine learning roadmap video So now, i have to follow your this video and your ML and DL course of 100 days or i have to follow roadmap resources? Which one ?
I am an Aeronautical Engineer who wants to be in Data Science and i am learning all the skills needed by Data Analyst just to get a job and get going in the data field is this the right approach.
12:05 #mistake no. 7 (wrong order of studying ML Algorithms) what did you said -> SBF(Selection By Filtering) OR SVM (Support Vector Machine).....Please Reply
I mainly face problem in understanding deployment of models since I am from non CS background. I have a fair grasp and understanding of algos and statistics since I am a statistics student. Second thing is writing complex sql queries. I really face a hard time dealing with them.
I focused on only ml and I judge core python that was my mistake.... focused on only libraries which are like pandas ,numpy..etc In this field python is also more important....
Can you take a survey on the same topic and display results where most people make mistakes because what you said is true to core also if you post on website it helps learner to have a glance plus we get evaluation were majority goes wrong 😅
Sir pls make a video on k fold cross validation Sir maine abhut saara video dekha par usme acche se explain nahi Kiya gaya hai Aap ek video banao aur statistics par bhi video banao Apne playlist me dusre ka video daala hai Sir it's very important for me I am watching only your video , getting understand with your video only Humble request from honest student to best teacher
This is definitely a helpful video. A mistake that I think I made was rushing too quickly into coding and not focussing more on basic stuff like MS Excel and SQL. Edit: Trying to land my first data role ever.
Guys I will recommend you for this course: Core Python (Hindi): ruclips.net/p/PLbGui_ZYuhigZkqrHbI_ZkPBrIr5Rsd5L Advance Python (Hindi): ruclips.net/p/PLbGui_ZYuhijd1hUF2VWiKt8FHNBa7kGb
Sabse badi galti ki kisi bhi institute ko bina sonche samjhe ya research kiye Bina join kar lena. Human nature hota hai ki first impression me agr koi chiz acchi lagi to hum usey hi consider krte hai aur isi cheez ka sales person advantage utha te hai. Before enrolling for any course try to ensure ki unka product kesa hai fomo me aakey join na kro. Aur Mentor ko khojne ki zrurat nahi hai wo yaha maujood hai sab Eklavya ban jao ab....
The biggest mistake I have done so far is that I became a perfectionist. In my opinion, you should find how much knowledge is important to just start and Practice, Practice, Practice. So that while practicing you will automatically start googling thing and learn.
1-> Not eating from one plate jumping here and there and last getting sleep without eating required food. 2-> Not having an proper mentor and also not having an partner of study. 3-> Not following a particular roadmap. 4-> Having so many resources to learn but don't know how to consume the efficient one with immediate effect. yet many others are there
My mistake is to aim for perfection instead of completion.. learning the same thing in multiple ways which drains so much of time ..Research thodi kr rhe hain itna time bithane ke liye... Learning --Implementation---Learning--Growing .. cycle should be like this. And my other mistake is to ignore deployment of models
Mistakes
1) False expectations
2) Not following single roadmap
3) Lack of consistency
4)ignoring pillars of data science -python, sql and statistics
5)ignoring pillars of data science-Data Preprocessing, feature engineering ,exploratory data analysis
6) Not working on real-world datasets
7) wrong order of study(ML algorithms)
8) Not focusing on deployment
9) not starting interview preparation on day 1
10) not having mentor or study group
Mistake done by me while learning DS/ML/Python:
Memorizing syntax - I was thinking I should write code without using google. Even in interview no one expects correct syntax from you, all they expect from u is how much you know concept. Though you must know basic syntax to clear coding round.
1. Revising python libraries again and again. It is a high possibility that you may forget the numpy pandas operations during execution. So you just need to take overview of code from internet and eventually you will start remembering them after 8-10 datasets.
2. Consistency - For this spiral method works which sir suggested i.e first take overview of topic and then do the topic again (Its like ek ek karke dhaage kholna)
3. No friends to study and never tried to talk with random.
Extra:
4. Mental Health - Jabtak dimmag shaant nahi rahega , business wala dimaag nahi chalega aur fir data science mein maza bhi nahi aega.
totally agree , i spend 1 month ,and each of its day in frustration ,as i wanted to cover so many topics in one day.
could you be my mentor plz
Love you bhai ❤️
I haven't aced any interviews yet but aced all these mistakes Thank you for bringing these small(but big) mistakes into light.
I have done all these mistakes and was demotivated. I will start again after watching this video. I purchased your DSMP 2.0 program. I found a good teacher now but very late.Thank you for being so honest in your teachings and making ML concepts easier for us.
1. Changed my roadmap quite a few times, which slowed my learning drastically. I think I studied same Pandas, Numpy, data viz libraries more than 2-3 times, but studied the same thing just for this mistake.
2. Inconsistency. I learnt, I stopped, and I forgot. And again the same circle!
I am doing all these mistakes but thanks for this video now i know what i need to know or focus on
I'm following your machine learning roadmap from start to end. And deep learning is still going on. Thank you sir ❤
The video was like a mirror for me .
I realised I was doing the same mistakes, but still in my learning phase so I can rectify it.
Thank you so much for sharing
Now i am realising that I am doing same kind of mistakes.
Thank you so much.
Great to know about you were a software developer !
It gave a quite motivation 😊
Sir i have followed all your course and for me you are best teacher regarding data science. I want you to create a playlist on model deployment and integration into website, android app and desktop application.
All most all mistakes i have experienced from from same bhai.. and started over coming from them... any way thanks for sharing without any hesitation.... 👍
1. Set fair time period to learn
2. Stick to one Roadmap
3. Consistency
4. Masters the pillars of data science (Python, SQL, Statistics & Maths)
5. Master -> Data Preprocessing, Feature Engineering, Exploratory Data Analysis
6. Try to work on Real Life Datasets
7. Give much time learning important ML algorithms
8. Deployment and management of Model
9. Prepare for interview simultaneously after learning anything
10. Motivation by mentor/study groups
I will be following your advice religiously from now on bro, thank you sharing these invaluable knowledge and tips
Hi bro are you getting started in data science we can connect on linked on
Thank you sir, for the roadmap. Your videos are really good, to be frank it is perfect for people like us who are from non-technical background.
3-Pillars Python, SQL , Maths(Stats, Linear Algebra, Probability)
TOP 10 Machine Learning Agorithms
Linear regression
Logistic regression
Decision tree
SVM algorithm
Naive Bayes algorithm
KNN algorithm
K-means
Random forest algorithm
Dimensionality reduction algorithms
Gradient boosting algorithm and AdaBoosting algorithm
Comment if Order is right, As I have just copied it from google.
1 KNN 2 naive bayes 3 linear regression 4 logistic regression 5 linear SVM 6 dual form of SVM 7 gradient descent 8 decision tree 9 random forest 10 GBDT 11 ada boost 12 Xgboost 13 PCA 14 t sne
you miss the main one merge the skills with different business domain
Mistakes in my DS journey 1. Focussing on implementation rather than in-depth knowldege. 2.Not getting into depth of things/ Having a superficial approach. 3. Thinking I understood it without actually understanding
the same situation is going with me, thanks for guide.
ye 10 points bahut zyada kaam ane wale hain...bahut zyada...shukriya nitish bhai ❤💯
Thanks for sharing this useful knowledge
I am master student in AI and all these things in my cirruculam 1. mistake I have not done learn theory that spoil time to learn practical and practice again so try both things parellel....theory and its practice
I was learning ML for about a year (to be honest I was frustrated)and I saw this video, I am committing 6 out of these 10 mistakes. Thanks to him for letting me know what I was missing. In the last part where he mentions that one should have a mentor or a study group, I totally agree with that and that someone who wants to team up is welcomed.
I'm new to ml ,will u team up?
@@mysterysoul1936 sure we can
@@vedantbhenia9085 where can we start and communicate?
I too have the same story as you. I too am learning for over a year with lot of inconsistency.
I want to team up if its fine with you.
I also want to be in team,
Please add me too
You have covered the syllabus along with mistakes. Syllabus is huge
Thanks!
Thank yoy so much this will be extremely helpful for me.
Bhaiya thanks, mentor nahi mila aap kai jaisa.
This channel is underrated
Your content is so valuable.....you must get millions of viewers
One day you will be
Thanks
I think you have covered all common mistakes that anyone can do or have done in past. Apart from this, I think one can also be distracted by some other courses just by seeing their salary and scope or may lose hope by seeing any negative feedback or review about data science. So, if you have decided to become a data scientist then remain stick to the course until you got a start in this field
I am following your roadmap , Thank you so much
We r very lucky to have a mentor like u sir. Very greatful to u n ur channel. Thanku so much. I did same mistakes u told. Still learning. Now that ur channel is there , i stay motivated.
Biggest mistake not having mentor like you yet
Yes you are right.
It's been almost 3 months i have started learning n practicing data science stuff trust me doing simple exploratory analysis on real world data is very difficult compare to learning ml dl models n maths
Great video....I just started learning Data Science.....This video will really help me not make these mistakes. If anybody is also like me who have just started can connect to me to form a study group.
how's your journey going??
Correctly said Bhai, inconsistent, less practice are my mistakes. Now i need to work on because I am from Non-tech background.
While watching videos it looks like a cakewalk but in real it's not!!
very informative video. 🙏🙏🙏🙏
Bahut achchha video hai guys
Nice advice bro...you saved tones of time
Thank you sir ....
plz sir time series forecasting p video bnao.
Please made a vedio on open source contribution in field of data science
Me bhi yhi mistake kr rha hun 6 months me data science khatm...aapka roadmap sahi he ....consistent ni hona ek ar galti ...python ,sql ,statistics strong krna ye sahi baat he ...data clean krne pe aaj se focus rahega maximum....real world data set and pe abhi tak me try ni kiya ........interview preparation wali baat sabse important .........thanks for this suggestion
Thank you sir for your valuable lessons
That's some extremely good advice. Thank a lot for this.
Can you please make a playlist of end to end project using real time dataset .
heyy learners and nitish sir too i m following youtube vedio only is it sufficient to learn or DSMP 2.0 is really much more conttent please reply on it that will be greatful.
Thankyou so much 😊✨🌼
Thanks for these priceless tips Legend Nitish Sir
Thankyou sir, I am following your Roadmap. Sir, can you please update the roadmap since you said you will update some more things.
Sir, ek deep learning roadmap
Hi sir, i am new to your channel from machine learning roadmap video
So now, i have to follow your this video and your ML and DL course of 100 days or i have to follow roadmap resources?
Which one ?
Roadmap
Loved to see you ❤️ awesome job brother
I am an Aeronautical Engineer who wants to be in Data Science and i am learning all the skills needed by Data Analyst just to get a job and get going in the data field is this the right approach.
Why are you come to data science filed?
@@atharvkumar9740 Because I am Interested
12:05 #mistake no. 7 (wrong order of studying ML Algorithms) what did you said -> SBF(Selection By Filtering) OR SVM (Support Vector Machine).....Please Reply
He said SVM
Nice advice..... it helps a lot..
I mainly face problem in understanding deployment of models since I am from non CS background.
I have a fair grasp and understanding of algos and statistics since I am a statistics student.
Second thing is writing complex sql queries. I really face a hard time dealing with them.
I focused on only ml and I judge core python that was my mistake.... focused on only libraries which are like pandas ,numpy..etc In this field python is also more important....
could you be my mentor plz or suggest any
U saved my life thankyou ❤️
sir please make a full data science roadmap for us🙏🙏🙏🙏🙏🙏🙏
Though i have already done most mistakes but I'll try to improvise them from now onwards.
Can you take a survey on the same topic and display results where most people make mistakes because what you said is true to core also if you post on website it helps learner to have a glance plus we get evaluation were majority goes wrong 😅
Is Data science field bright in 2023?
Future scopes comparing others tech fields?
Sir pls make a video on k fold cross validation
Sir maine abhut saara video dekha par usme acche se explain nahi Kiya gaya hai
Aap ek video banao aur statistics par bhi video banao
Apne playlist me dusre ka video daala hai
Sir it's very important for me I am watching only your video , getting understand with your video only
Humble request from honest student to best teacher
Yaar ye kitna awesome hai 😅
This is definitely a helpful video. A mistake that I think I made was rushing too quickly into coding and not focussing more on basic stuff like MS Excel and SQL.
Edit: Trying to land my first data role ever.
Great mentor for me
I have ignored deployment. Need to focus on it.
I have done all this mistake, join creating any study group should be first thing I have to do.
Sir mai to apko naman karta hu...aap ban jao mere mentor
Thank you sir
Sir is 100days of machine learning playlist enough to crack machine learning interviews??
Amazing ❤
Guys I will recommend you for this course:
Core Python (Hindi): ruclips.net/p/PLbGui_ZYuhigZkqrHbI_ZkPBrIr5Rsd5L
Advance Python (Hindi): ruclips.net/p/PLbGui_ZYuhijd1hUF2VWiKt8FHNBa7kGb
Sabse badi galti ki kisi bhi institute ko bina sonche samjhe ya research kiye Bina join kar lena. Human nature hota hai ki first impression me agr koi chiz acchi lagi to hum usey hi consider krte hai aur isi cheez ka sales person advantage utha te hai. Before enrolling for any course try to ensure ki unka product kesa hai fomo me aakey join na kro. Aur Mentor ko khojne ki zrurat nahi hai wo yaha maujood hai sab Eklavya ban jao ab....
Thank you so much sir
Thank you so much ❤
Thankyou
Interview clear karne ke liye kitna syllabus padhna chahiye and kitna time lagega ?
I have statistics background my mistake is, do not practice regularly of coding.
Hello sir
Any recommendations or videos on deployment?
Sir i am a dropout will i get the job as data scientist?
Mistake 2 for me because I am learning data science
Sir why you are looking old in your new videos mujhe yeh dekh kay buhot dukh huwas
The biggest mistake I have done so far is that I became a perfectionist. In my opinion, you should find how much knowledge is important to just start and Practice, Practice, Practice. So that while practicing you will automatically start googling thing and learn.
be my mentor sir all other 9 mistake ill cover .
Good sir g thanks
you are true person
Felt like my future is talking with me ,i did the same mistakes which sir quoted.
Sir where did you learn data science, can u tell that ??
How much python is needed for data science or data analysis
He is telling exact facts
Dont try to finish python or any ML Subjects just in one setting or continues watching lecture without revision.
Sir i also started learning ml algo initially and was not knowing python sql. I face difficulties daily
2nd one happened with me as well...
My mistake was i saw many courses .. stick with only on which helps u
1-> Not eating from one plate jumping here and there and last getting sleep without eating required food.
2-> Not having an proper mentor and also not having an partner of study.
3-> Not following a particular roadmap.
4-> Having so many resources to learn but don't know how to consume the efficient one with immediate effect.
yet many others are there
data cleaning, Feature engineering, exploratory data analysis
Sir data science ky liay apko web development b ani chaheay?? Yeh skill b ana chaheay Like css html JavaScript?? Or only backend in enough
Ofcourse, You have to make web application according to your ML model so, you have well knowledge of web develpment.
Suppose I completed a topic eg mangoDB or stats. So where can I find projects related to the topics which I have completed?