Journey of MlOps (Machine learning + Operations)
Discuss about what we learn in this particular training?.
Before training of MlOps :-
I know little bit about machine learning, computer vision and python and solve the some algorithm like linear regression and classification problem.
After training of MlOps :-
MlOps training divide in some steps….
Step 1:- Learn about RHEL( Red-hat Enterprise Linux)
We start journey of MlOps we learn about basic of Redhat operating system and integrate with python, online live training mentor of Vimal Daga sir in this particular training we learn all the zero to advanced concept on operating system. This training is also part of my MlOps journey. In this we learn lots of about operating system like…..
Learn basic command:-
Installation of redhat in virtual box,ls, gedit, date,cal, ipconfig, ping,learn basic of ip-address, nslookup command, bc(binary calculator), learn about terminal, which command, ps -aux command, grep, kill, mkdir,cd, rm ,cat, startx, chvt,tty, echo, touch, learn package management, yum configuration, dnf configuration, learn about configuration of server, web-server configuration,Apache web server configuration,concept of firewall ,curl,systemctl, netstat -tnlp,discuss partition of hardisk, primary partition, physical partition. Many thing learn RHEL+ Python training.
Step2:- Start of Mlops Learning
1:-Computer Vision
In this we learn about how to work on image, How to use numpy librery to create image, learn Opencv library CV2, learn how to resize the image, learn webcame(live video capture). Learn how to crop the images and videos.Learn basic idea of image processing.Use Haarscade to face detection and learn idea of use behind the Haarscade.Learn yolo object detection algoritham or pre trained model to detect the models.
2:- Machine learning
In this area we start learn to library like numpy ,pandas matplotlib, learn how to read the dataset use of pandas library, use of numpy array work on matrices and learn matplotlib to visual the graph,Learn Linear regression,learn training and testing concept of dataset.Learn how to fit the model and how to predict the model.
Note:- Most important for me learn about one time run the model and save the model and use many time particular model. Model save in the file format of pk.
Learn linear regression algorithm.Lean main idea of linear regression concept. Learn how to find the absolute error and min error concept. Learn scikit-learn algorithm. Learn optimization concept of algorithm. Learn Multi linear regression algorithm.
Note:- Most important for me learn about Feature selection concept. Feature selection is two type Manually(Domain Expert) and Programmer , Lean base algorithm we use in feature selection is Filter method, wrapper method, Embedded method.
Learn how to find the correlation of columns in the dataset. Learn feature scalling concept.Learn heat map to find the NAN values in the dataset.
Note:- Work on Price dataset
Learn idea of coefficient.Learn idea of feature engineering.Discuss label encoding, categorical encoding, one hot encoding.
Note:- Most important for me Dummy Variable trap. Redundant and Duplicate concept.
Learn backward elimination concept, learn statistical analysis concept.Learn Hypothesis. Learn about Adj. R squared concept.
Learn tensor-flow and keras algorithm.Learn lazy execution. Learn distributing computing. Learn Deep learning concept perception ,neuron, Gradient descent.Learn auto feature selection.Learn activation function relu,sigmoid,Threshold,tanh etc..Discuss feed forward ,forward propagation, Back Prorogation. Discuss learning rate concept. Learn epoc concept. Learn gradient descent .Learn optimizer Adam etc..Learn data visualization Matplotlib,seaborn, pandas.
Note:-Most important for me Folium library to create Maps. Laern adaptive learning rate.
Learn classification algorithm.Binary classification.
Note:- Work on Titanic Dataset
learn confusions matrices.Learn plotly library.
Note:- Work on Bank Datset
step3 :- Deep Learning
In this we learn about basic of perception.Learn input layer, hidden layer, output layer.Discus single neuron and multi neuron. Discus about optimizer ,dense layer,learn binary cross entropy.Learn Multi classification algorithm. Learn about CNN(convalutional Neural Network) use to eliminate the feature , manually and automatically.
Note:- Work on MNIST Dataset
Learn VGG, Res-net, inception method of CNN algorithm.Learn Fine tuning and transfer learning.
Note:- Transfer learning is most important for me. Create few image to lots of dataset use augment concept.
Learn VGG16,VGG19,Mobile-net, freeze layer concept.Learn KNN Algorithm. Learn clustering algorithm,Learn Mask-R_CNN Algorithm.Learn GAN’S Algorithm.Learn Association rule.learn apriori algorithm and recommendation system concept.Learn RBM concept.
Step4:-Docker
Learn concept of Docker, installation of docker, download the docker images, launch the web-server use of docker image, docker networking.
Note:- Most important for me to create a docker image use of Docker-file concept.
Step5:- Git and GitHub
learn concept of git, git source code controller, learn how to create git repository and push on the github and store , git commit concept , git merge concept, git pull concept etc..
Step6:-Jenkins
Learn concept of Jenkins, use to Jenkins, copy the code on the GitHub.SCM concept, Poll SCM concept ,crone tab concept, Github, tunel cocept, plugin concept.
Step7:-Kubernetes
Learn concept of Kubernetes, Installation of Kubernetes, How to launch pods, Learn about minikube, learn replica set, learn yaml programming language, and cli command of kubernetes,learn concept of Replication controller, learn concept of replica set.
Solve some task on this MlOps journey:-
Task1:-https://medium.com/@neeteeshyadav98/task-1-automation-cb178b6dee4c
Task2:-https://medium.com/@neeteeshyadav98/jenkins-job-automation-45809e25e32a
Task3:-https://medium.com/@neeteeshyadav98/mlops-task-66a50108ed65
Task4:-https://medium.com/@neeteeshyadav98/integration-with-git-github-cec65fb4ec3f
In this journey we learn lots of things.I do’t have master level knowledge but i have knowledge all the concept, I have studied in this MlOps journey.May I choose to say thank you to every one help me in this MlOps Journey. Also thanks LinuxWorld india private limted to give opportunity to part of this program. This summer is best summer for me I learn lots of things in this summer.
Also thanks to Vimal Daga sir provide great knowledge and motivation to learn lots of thing and Think Like Creator, and thanks to Priti Mam to help each and every time. And thanks all Volunteer to help.
