Today's Progress: Spent most of the day reading up on regression. trying to prove autocorrelation, collinearity and creating graphs for the presentation.
Thoughts: Luckily i have Kat on my team. this short sprint would of suck if not for her.
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Today's Progress: Completed all the models, focus on SVR especially the rbf and poly kernels. helped Apollo team member with a function that was really interesting.
Thoughts: need to get back to codewars, or writing summary articles.
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Today's Progress: completed presentation slides, performed presentation and completed the report.
Thoughts: luckily i had Kat or this sprint would of been an epic fail.
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Today's Progress: completed chapter 4 of DS in Python
Thoughts: I will complete this book, but first focus on on classifiers
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Today's Progress: Chapter 2 of Intro to ML with Python.Supervised Machine Learning section. went over k-nearest neighbours and Linear Models.
Thoughts: I will start a notebook with a summary of each algorith, the benefits and when to use. as well as sample code and pipelines.
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Today's Progress: Wrote summaries of k-NN and Decision Trees as well as Ensemble methods
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Today's Progress: completed Network analysis thereby completing the datsci track of DataCamp!!
Thoughts: It is a really good track. found it very useful, but revision is key as I forgotten alot of it. Luckily it is easier to review than learn from scratch :)
Today's Progress: Went through Linear models and SVMs in supervised learning in Intro to ML with Python
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Today's Progress: did two problems in CodeWars. Went over GridSearch, cross-validation and Pipeline.
Thoughts: I am hoping to master GridSearch and Pipeline to speed up modeling.
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Today's Progress: summarizing Linear models for regression and classifying. Started the NLP in python course
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Today's Progress: finished chapter on sentiment analyzer
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Today's Progress: Started the NLP course in Udemy
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Today's Progress: Completed NLP in Python from DataCamp
Thoughts: It'sa very good intro course. There's alot to learn on the topic. I need to find a thorough course on NLP
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Today's Progress: Completed the NLP course in Udemy
Thoughts: This course doesn't leave one with much confidence in coding nlp techniques. will go over the nlp sections in other courses
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Today's Progress: Completed NLP sections in both the DatSci AZ and DatSci ML Bootcamp.
Thoughts: I will start implementing some nlp processing tomorrow.
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Today's Progress: Completed kNN, SVM and kernel SVM sections in both the DatSci AZ
Thoughts: starting with regex section in Colts Python3 Udemy course.
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Today's Progress: Completed the RegEx section of Colt. Completed the Linear Classifiers in Python course in DataCamp
Thoughts: Tomorrow I will put my knew regex knowlede to preprocess the mbti text dataset.
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Today's Progress: I wrote all the individual functions for creating each feature in the dataset, then combined them all in a single function. regex really usefull.
Thoughts: I found a great blog that had regex exercises. will include them in my summary to drill the concepts into memmory
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Today's Progress: Finished summary of kernel SVM, worked on plotly charts; bar charts.
Thoughts: west through the layout lectures of Dash. it is not complocated, although the syntax is intimidating with all the nested dictionaries.
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Today's Progress: Completed the rest of the plotly charts and moving on to actual Dash. Completed the third section of Time Series analyses of DataCamp.
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Today's Progress: went over Dash layout, html and core components. Created my own stopwords list for the Personality profile sprint. and started thinking about pipelines and working out a strategy.
Thoughts: Dash is very interesting. will look into hosting the server on raspi, as well as finding a great project to practive what i have learned.
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Today's Progress: Did the baseline result using countvectorizer and multinomialNB. played with a few parameters and results were dismal. Researched FeatureUnion, functionTransformer to join my created features along with countvectorizer to train the model.
Thoughts: I am probably going well above what's expected but learning about featureUnion is helpful in expanding my knowledge.
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Today's Progress: I built functions to get numerical and text data used functionTransformer to be able to use them in a pipeline. built text and numerical pipeline and merged them with FeatureUnion into main pipeline
Thoughts: after successfully creating main pipeline, had errors with the text part after creating y_labels (therefore creating binary labels)
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Today's Progress: struggled half the day trying to solve the main pipeline issue. gave up after mega headache.
Thoughts: starting over, concentrating on just nlp for the model. then include numerical features.
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Today's Progress: not feeling very well, went over Dash and started a new course on algorithms and interview questions
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Today's Progress: went over Dash, built an interactive display using a range slider and outputting to a div.
Thoughts: I'm thinking of reviving the dc enviro project using dash instead of highcharts. I'm using flask anyway.
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Today's Progress: got a working model using Random Forest. basic settings, need to do gridsearch on hyperparameters.
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Today's Progress: started over building a function to run through all the pipelines and taking into account the time to train. Next is working on gridsearch to fine tune the parameters.
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Today's Progress: working hard on the personality sprint project. all fell apart but was able to plan a b c d it and managed to complete and meet the deadline!
Thoughts: I learned so much this sprint but prolly performed the worst ironically...
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Today's Progress: Spent most of the day prepping the presentation, creating wordcloud, and gaining insights into the data
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Today's Progress: Presentation day! went well. last minute prep and nlp insights gathering really helped. Started The Tensorflow Udemy course and finished the intro.
Thoughts: I was exhausted, individual project stress took its toll. then two of us carrying the rest of the team meant added pressure and stress. glad it's over.
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Today's Progress: Nearly completed Tensorflow basicss and starting the exercises.
Thoughts: The estimator api seems really simple. will implement the previous classification problem using tensorflow estimator api.
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Today's Progress: Completed Tensorflow basics and completed the reg and classification exercises.
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Today's Progress: Started on CNN, convoluted neural networks. need to go over the example.
Thoughts: I started exploring the movies dataset and need to plan the layout of the dashboard.
Today's Progress: completed the first two sections of Kaggles Learn Pandas section; reading and creating df's, and indexing and selecting.
Thoughts: I plan to complete all 7 by the end of review week
Today's Progress: I've gone through the CNN section of the tensorflow course. gone through the exercise solution. read ISLR chapter 8; trees and ensembles
Thoughts: I hope to build an initial model early on, so that i can trial others and iterate through to the winning model
Today's Progress: I completed 27 exercises on functions and another 3 on dictionaries
Thoughts: picked up cool tricks,
Today's Progress: I completed all exercises on dictionaries, wrote a notebook for reference and reviewed lists and sets
Thoughts: I will make short posts on lessons and other examples with which to apply them.
Today's Progress: Reviewed advance features of lists, sets and dictionaries.
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Today's Progress: Started another DL course 'Deep Learning A-Z' on Udemy, went through the first chapter.
Thoughts: Using Keras is SO much simpler that TF. I think learning and aplying Keras will be better to get started using DL, and then learn TF proper in case i need to go deeper.
Today's Progress: I completed the Forward feed NN chapter from DL A-Z, learned to crossval and gridsearch using the keraswrapper and scikit-learn.
Thoughts: I need to find a few basic datasets to test my usage of coding a NN. maybe from the datasets used in ML A-Z course.
Today's Progress: Gone over Decision Trees and Random Forest from ML A-Z.
Thoughts: Reading an article on embedding ML in a webapp i came across batching huge data and training the model sequntially using .partial_fit()
. waiting on the next article where the writer uses flask to run the webapp.
Today's Progress: I spent most of the day reviewing kaggle kernels on predicting games.
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Today's Progress: Built a basic model to predict results. Then refactored it into a function.
Thoughts: Now that I have a basic model, I can build one with more vairables and hopefully more accurate.
Today's Progress: terrible migraine. not much work done
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Today's Progress: None.
Thoughts: Eid. took a well deserve break and spent the day with family and friends.
Today's Progress: Did most of the Baye Test Due tommorow night. Went over the intuition for word2vec.
Thoughts: Found Sendex tutorial on Dash, checking what he has to add
Today's Progress: Fathers day, gone for half the day. but i was left alone for few hours to complete the rest of the test.
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Today's Progress: Completed the Bayes test 70% -not great, but ok. Got my AWS working, but we using a colleagues as the central db to work from. Went over the train document on building a world cup model and using simulation.
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Today's Progress: I completed the pythonhow challenge. instructions abit unclear, but with some motivation from the discord chat i completed it.
Thoughts: finding it difficult to power through building a model. going to rest tonight and make sure i have a working one tomorrow night
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Thoughts: review pending
Today's Progress: mastering sql
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Today's Progress: leaning api
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Today's Progress: learning selenium and apis
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