Hi, Well come to Fahad Hussain Free Computer Education Here you can learn Complete computer Science, IT related course absolutely Free! Machine learning is the part of artificial intelligence (AI), and this is further divided into Three (03) parts:
Supervised Learning
Unsupervised Learning
Reinforcement Learning
We will cover the all types of Machine learning (stunning and very well known algorithms) using Python.
The whole course base on the concept of Theory and Practical! For Further Assistance and code visit: https://fahadhussaincs.blogspot.com/ For Complete course YouTube Channel: https://www.youtube.com/channel/UCapJ...
Whole Sessions' Tutorial Slides,
Click to download!
Supervised Learning
Unsupervised Learning
Reinforcement Learning
We will cover the all types of Machine learning (stunning and very well known algorithms) using Python.
The whole course base on the concept of Theory and Practical! For Further Assistance and code visit: https://fahadhussaincs.blogspot.com/ For Complete course YouTube Channel: https://www.youtube.com/channel/UCapJ...
Whole Sessions' Tutorial Slides,
Click to download!
Session / Tutorial No. 01:
Click to WATCH the Series of Videos
First Session is based on Theory, What is AI, ML, DP... you can get presentation slide upon your request through comment!
Session / Tutorial No. 02:
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Its all about Data Preprocessing in Python using Dummy Data set... Click to Download the Data_Set including the Code!
Session / Tutorial No. 03:
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This Session is based on Theory, different types of machine learning.... including the concept of Regression and its types (theory), you can get presentation slide upon your request through comment below!
Session / Tutorial No. 04:
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What is linear Regression...
Session / Tutorial No. 05:
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What is Multiple linear Regression...
Click to Download the Data_Set including the Code!
Session / Tutorial No. 06:
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What is Polynomial linear Regression...
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Session / Tutorial No. 07:
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What is Support Vector Regression...
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Session / Tutorial No. 08:
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What is Decision Tree Regression...
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Session / Tutorial No. 09:
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What is Random Forest Regression...
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Session / Tutorial No. 10:
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Evaluation metrics machine learning to checkout the accuracy and error by using different techniques... Click to Download the Data_Set including the Code!
Session / Tutorial No. 11:
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Evaluation metrics machine learning to checkout the R Square and Adjusted R Square differences and definition...Click to Download the Data_Set including the Code!
Session / Tutorial No. 12:
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What is Classification, how does Logistic Regression Work... Click to Download the Data_Set including the Code!
Session / Tutorial No. 13:
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Let's understand about the KNN Classification Theory and Practical... Click to Download the Data_Set including the Code!
Session / Tutorial No. 14:
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Support Vector Classification, Theory and practical...Click to Download the Data_Set including the Code!
Session / Tutorial No. 15:
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Support Vector Kernel Trick! Just exchange the parameter linear to rbf, the rest of the code same as Session no. 14 Code, which can be download from the Session / Tutorial No. 14
Session / Tutorial No. 16:
Naive Bayes Theorem/Classifier, including the concept of different types of Naive Bayes model, Theory and practical... Click to Download the Data_Set including the Code!
Session / Tutorial No. 17:
Decision Tree Classifier, its all about the Theory Concept of DTC, you can demand free slide which has been used in the theory session via comment below...
Session / Tutorial No. 18:
Session / Tutorial No. 19:
Decision Tree Classifier by Gini Index, its all about the Theory of DTC by gini index...
Session / Tutorial No. 20:
Decision Tree Classifier by gini index, practical session...Click to Download the Data_Set including the Code!
Session / Tutorial No. 21:
Its all about Ensemble Learning, Bagging, boosting and stacking with the concept of random forest classifier. Get presentation slide on your demand through comment below...
Session / Tutorial No. 22:
Its all about Theory session on under-fitting and over-fitting...
Session / Tutorial No. 23:
Random Forest Classifer practical session
Click to Download the Data_Set including the Code!
Click to Download the Data_Set including the Code!
Session / Tutorial No. 24:
Its all about Evaluation metrics for classification using sklearn get presentation slide on your demand through comment below...
Session / Tutorial No. 25:
Its all about Evaluation metrics for classification using sklearn practical using IRIS dataset to make it understand in a better way.. Click to Download the Data_Set including the Code!
Session / Tutorial No. 26:
Its all about clustering definition, and K means clustering type, in theory, get presentation slide on your demand through comment below...
Session / Tutorial No. 27:
K Means Clustering in python PRACTICAL SESSION practical session
Click to Download the Data_Set including the Code!
Click to Download the Data_Set including the Code!
Session / Tutorial No. 28:
Hierarchical clustering in machine learning (Theory) | Agglomerative hierarchical, in theory, get presentation slide on your demand through comment below...
Session / Tutorial No. 29:
K Hierarchical clustering PRACTICAL SESSION practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 30:
Its all about Agglomerative VS divisive hierarchical clustering in theory, get presentation slide on your demand through comment below...
Session / Tutorial No. 31:
Its Density Based Clustering (DBSCAN) Theory 1 in theory, get presentation slide on your demand through comment below...
Session / Tutorial No. 32:
Density Based Clustering (DBSCAN) PRACTICAL SESSION practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 33:
Its Hard clustering VS Soft Clustering | What is Clustering and its different algorithms, get presentation slide on your demand through comment below...
Session / Tutorial No. 34:
Its Association rule mining | Apriori Algorithmand its different algorithms, get presentation slide on your demand through comment below...
Session / Tutorial No. 35:
Apriori Algorithm in Python PRACTICAL SESSION practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 36:
Its Eclat Association Rule Learning, get presentation slide on your demand through comment below...
Session / Tutorial No. 37:
Eclat Algorithm in Data Mining using Python PRACTICAL SESSION practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 38:
Its FP growth Algorithm in Data mining, get presentation slide on your demand through comment below...
Session / Tutorial No. 39:
FP Growth Algorithm using python PRACTICAL SESSION practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 40:
An introduction to Reinforcement Learning, get presentation slide on your demand through comment below...
Session / Tutorial No. 41:
Session / Tutorial No. 43:
Markov Decision Process, Bellman Equation, Q Learning in Machine Learning, get presentation slide on your demand through comment below...
Session / Tutorial No. 44:
Sarsa in reinforcement learning | On-Policy VS Off-Policy in Reinforcement Learning, get presentation slide on your demand through comment below...
Session / Tutorial No. 45:
Multi armed bandit Algorithm using Upper confidence bounds | Single Arm bandit, get presentation slide on your demand through comment below...
Session / Tutorial No. 46:
(Practical) Multi armed bandit Algorithm using Upper confidence bounds (Random Selection, with UCB) practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 47:
(Theory) Thompson sampling multi-armed bandit problem | Thompson Sampling, get presentation slide on your demand through comment below...
Session / Tutorial No. 48:
(Practical) Thompson sampling multi-armed bandit problem | Thompson Sampling practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 49:
(Dimensionality Reduction and its types | PCA, principal component analysis explained practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 50:
(Dmensionality Reduction and its types | LDA, Linear Discriminant Analysis explained practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 51:
(Dimensionality Reduction and its types | KPCA, Kernel principal component analysis explained practical session Click to Download the Data_Set including the Code!
Session / Tutorial No. 52 & 53:
Cross Validation and its types Theory and practical session (part I, II), Click to Download the Data_Set including the Code!
Session / Tutorial No. 54:
Grid Search with K Fold cross validation theory+Practical , Click to Download the Data_Set including the Code!
Session / Tutorial No. 55:
XGBoost, theory+Practical , Click to Download the Data_Set including the Code!
Session / Tutorial No. 56:
The Wonderful journey of Machine Learning come to END here, Now stay in touch, Deep Learning course from scratch will be started SOON, till then Enjoy Learning....
sir pls ur cell no and where u r
ReplyDeletewe need research guidence in ML
Dear I cannot share my contact number, but you can write comment when you feel trouble regarding your research topic :)
Deleteplz sir slides share kar dain...
DeleteSend me your slides plz respected sir
DeleteSalam Sir You are doing great job .
DeleteFrom where i can find the codes.
Brother please upload rest of the lectures slide,dataset and code.Many many thanks .
ReplyDeleteAll the datasets and code sent already, and at the starting of this page I also upload the slide from there you can download :)
DeleteSir Namskar, is it possible give me presentation slide for better reading and revision.
ReplyDeleteRegard and thanks a lot
Its uploaded now, get download and enjoy!
Deletesir link please share kar den
DeleteThanks a lot, I always like your tutorial and way of explanation. Good service to society
ReplyDeleteThanks, do share to others learners...
Deleteits awesome work for beginners
ReplyDeleteThanks...
DeleteHello sir, Please I need the slides and sample code for the machine learning. Thank you
ReplyDeleteIts uploaded now, get download and enjoy!
Deletethanku so much sir fahad hussain , your way of teaching is remarkable just like sir nasir hussain(PIAIC leading teacher). Thanku for this machine learning tutorials
ReplyDeleteThanks, do share to other learners...
Deletewhere all the slides are uploded and great job fahad sir
DeleteDo I have to learn Python first before starting this?
ReplyDeleteYes, but if you know about R programming language, you can do this, else need to learn Python First...
DeleteSir can you explain EDA for data science ?when we use Multicollinearity and how will deal with multiple categorical variables.
ReplyDeleteHello respected Sir!
ReplyDeleteI need help from you on a topic that is:
(graph embedding/graph representation in machine learning)
sir if you any video or lecture on this topic so kindly shared that one please
Masha Allah , Definitely its going to be a wonderful journey ,as I already learned data science from IBM Professional, and wanted one thing for practise , its very good option and for those who dont want to spend money to institutes , secondly at least as per my knowledge no institute in Lahore is offering this type of knowledge as I get admission in some top institute of lahore, and a doctor (PHD) guy is teaching there (also enrolled in big data as well in 2 months course we just installed hadoop and hive and both are not working) and they said that your 16 lectures has been completed and course is off now, We all group is in wonder that what we learned ? so Again thanks that you are offering your services to the neddy ones. May Allah Bless u with more health , wealth and Emaan.
ReplyDeletesir data set chay?
ReplyDeleteclick to download from up side of the same page...
Deletecan you please forward ppt of eclat algorithm tutorial no 37 at
ReplyDeletepoonamgaba86@gmail.com
From where i can find slides? I am not able to find it in your blog sir
ReplyDeleteSir i am not able to download dataset / code rar file... kindly suggest
ReplyDeletesir,
ReplyDeletewhen i type import numpy as py or 5+5
I am not able to run this code...and not getting the o/p 10 in console
output shown on console is
:-- runcell(0, 'C:/Users/hcl_pasharma/untitled5.py')
...I am not able to run the code....can you assist. its urgent
Sir, Kindly share the slides to go through the topic for quick reference
ReplyDeletegood work man! keep it up.......
ReplyDeletehi,how are you?
ReplyDeleteEid Mubarak! sir can you share slides with me
salam sir! sir i want that a small project on the machine learning.
ReplyDeleteit will built our knowledge.
great tutorials.
ReplyDeleteTHE BEST!
ReplyDeleteHi Sir (Fahad),
ReplyDeleteI am practising end-to-end machine learning using python.
How to made easily configurable to enable easy experimentation of different algorithms and parameters as well as different ways of processing data (e.g. usage of a config file, environment variables, or command line parameters) so that I can evaluate performance of different models before deciding to take the best model for further hyperparameters tuning?
Thank you in advance for the advice and help.
Sallam Fahad,
ReplyDeleteyour tutorial and understanding method is very comprehensive. I will appreciate if you could share all the Machine learning tutorial slides. It difficult to write every thing from video.
Thanks in advance
Thank you in advance for the advice and help
ReplyDeleteHello Fahad @ pleasure to connect with you.
ReplyDeleteWell i learnt a lot from your video, somewhere now i'm feeling more confident to do more research in AI.
Well, just want to say thanks for all.
If could be possible to share the Slides of the series, that would really more helpful for me to understand more deeply.
Thanks again.
Stay Tuned.
I will be waiting for your next deep learning series.
Sir, you are really true mentor for data science.
ReplyDeletesir:, where is genetic algorithm use usually?
ReplyDeletehi, your google drive link is not working!!!
ReplyDeleteAssalam o Alikum! Sir your course of ML is just Awesome.I need your slides of machine learning .Also i want to request you to upload lectures of Data mining
ReplyDeleteGoogle drive link is not working .Please share it so can I download dataset
ReplyDeleteIlearnt a lot from your video, now feeling more confident to do more research in AI. Could you share me the slides to me for Machine learning and data science?
ReplyDeleteRegard and thanks a lot
Sir kindly share your email id
ReplyDeletesir,
ReplyDeletei am doing PhD in mechanical Engineering. i want to use ANN with python for prediction of my experimental values. 6 input and 2 outputs..pls provide me coding
Sir, please provide me code for either c4.5 or ID3 with 8 parameters and 1 output. I need to incorporate to validate my framework.
ReplyDeleteSir thanks for your lecture please help me for the notes for decision tree classifier part 1.
ReplyDeleteDear Sir
ReplyDeletein tutorial of apriori algorith we see only our pair of item which sell together but as a data scientist what stock should I kept in mall,grocery shop so that it fulfill customer requirement according to transaction basis and also some item like bread with milk has 2 to 3 days of expiry than what algorithm I used to keep our 2 to 3 days stock according to that transaction.
Dear Sir
ReplyDeletein tutorial of apriori algorithm we check only pair of our selling item according to transaction but as a Data Scientist what stock should I kept so that there is not any shortage of our items and also some items like bread with milk has 2 to 3 days of expiry in point of this also what algorithm I used so that it fulfill our customer requirement according to that transaction
Sir plz send me link of auto encoders ppt. THANK YOU
ReplyDeleteBrother can you share some material or usefull link regarding solving these problems through mathemtics on paper
ReplyDeleteSir please solve some kaggle problem.
ReplyDeleteYour lecture video is awesome finally i found video where i can understand all concepts in easiest way.
sarsa algorithm code?
ReplyDeletebro can please share slides of GAN on email
ReplyDelete13279263560@QQ.COM
Hi sir . Salam
ReplyDeleteGreat job . Sir I need the presentation slides.
Hello sir all your videos are fabulous please upload full end to end project of data science if it is possible like from accessing data from SQL server and than data preprocessing, making machine learning model and hyper parameter tuning and deployment please make a full video end to end process. Thanks
ReplyDeleteAsalamu alaikum brother
ReplyDeleteI cannot find ppt for ML course
Can you please tell me how can I get ?
for machine learning practical lectures kindly tell me which version of anaconda python you used and spyder version and scikit-learn version ?
ReplyDeletebecause in latest versions when we run code lots of errors.
so kindly mentioned the
1. anaconda python version
2. spyder verson
3. scikit-learn version
so same code will be excuted.
thanks
Respectede Sir I need lecture slides of lecture Session / Tutorial No. 41
ReplyDeleteAoa dear. I am having trouble in onehotencoder command. It seems like it has become obsolete kindly tell its alternative in python 3.9
ReplyDeleteHi sir can u send me the ppt of the machine learning like u send the deep learning ppt in drive
ReplyDeleteAssalamvalekum sir please share complete course ppt
Deleteof machine learning using python
can you make videos of cnn hyperparameter tuning using metaheuristic algorithm using statiscal dataset like iris or stock
ReplyDeleteGreat videos! Could you kindly send me your slides? Thanks!
ReplyDeleteBrother Fahad, would you like to share the Slides(ppt's) link, so we can have the more benefit, undoubtely your lectures are remarkable and few are incredible. Allah may bless you and all practitioner Muslims.
ReplyDeleteEspecillay I would like to suggest you to be on Udemy and Upwork, InshaAllah you will earn a lot.
Regards
Kashif
Dear Kashif, its already shared at the top of this web-page -Click to download-
DeleteBrother Fahad, would you like to share the Slides(ppt's) link, so we can have the more benefit, undoubtely your lectures are remarkable and few are incredible. Allah may bless you and all practitioner Muslims.
ReplyDeleteEspecillay I would like to suggest you to be on Udemy and Upwork, InshaAllah you will earn a lot.
Regards
Kashif
Dear Kashif, its already shared at the top of this web-page -Click to download-
Delete