Today's Progress : I have setup all the things needed to learn Machine learning. I have decided to use google colab for coding. And also found some interesting tutorials online.
Today's Progress : Started reading the book Hands on Machine Learning with Scikit Learn and Tensorflow and finished the first chapter.
Today's Progress : Learned Exploratory Data Analysis(EDA) from here
Today's Progress : Learned about Dimensionality Reduction and Visualization from appliedaicourse.com
Today's Progress : Learned Principal Component Analysis(PCA).
Today's Progress : Started a course on Foundations of Machine Learning on Bloomberg. Finished the first lecture and learned about some basics of machine learning.
Today's Progress : Finished the second lecture CASE STUDY: CHURN PREDICTION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the third lecture INTRODUCTION TO STATISTICAL LEARNING THEORY in the Bloomberg Machine Learning Course.
Today's Progress : Finished the fourth lecture STOCHASTIC GRADIENT DESCENT in the Bloomberg Machine Learning Course.
Today's Progress : Finished the fifth lecture EXCESS RISK DECOMPOSITION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the sixth lecture L1 AND L2 REGULARIZATION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the seventh lecture LASSO, RIDGE AND ELASTIC NET in the Bloomberg Machine Learning Course.
Today's Progress : Finished the eigth lecture LOSS FUNCTIONS FOR REGRESSION AND CLASSIFICATION in the Bloomberg Machine Learning Course.
Today's Progress : Learned the basics of Numpy. And also finished the ninth lecture LAGRANGIAN DUALITY AND CONVEX OPTIMIZATION in the Bloomberg Machine Learning Course.
Link of Work: Commit
Today's Progress : Finished the tenth lecture SUPPORT VECTOR MACHINES in the Bloomberg Machine Learning Course.
Today's Progress : Finished the eleventh lecture SUBGRADIENT DESCENT in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twelfth lecture FEATURE EXTRACTION in the Bloomberg Machine Learning Course. And also learned the basics of matplotlib and implemented them.
Link of Work: Commit
Today's Progress : Finished the thirteenth lecture KERNAL METHODS in the Bloomberg Machine Learning Course.
Today's Progress : Finished the fourteenth lecture PERFORMANCE EVALUATION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the fifteenth lecture "CITYSENSE": PROBABILISTIC MODELING FOR UNUSUAL BEHAVIOR DETECTION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the sixteenth lecture MAXIMUM LIKELIHOOD ESTIMATION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the seventeenth lecture CONDITIONAL PROBABILITY MODELS in the Bloomberg Machine Learning Course.
Today's Progress : Finished the eighteenth lecture BAYESIAN METHODS in the Bloomberg Machine Learning Course.
Today's Progress : Finished the nineteenth lecture BAYESIAN CONDITIONAL PROBABILITY MODELS in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twentieth lecture REGRESSION AND CLASSIFICATION TREES in the Bloomberg Machine Learning Course.
Today's Progress : Learned Logistic Regression and implemented it to solve Titanic: Machine Learning from Disaster problem on Kaggle.
Link of Work: Commit
Today's Progress : Finished the twenty first lecture BASIC STATISTICS AND A BIT OF BOOTSTRAP in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twenty second lecture BAGGING AND RANDOM FORESTS in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twenty tird lecture GRADIENT BOOSTING in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twenty fourth lecture MULTICLASS AND INTRODUCTION TO INSTRUCTURED PREDICTION in the Bloomberg Machine Learning Course.
Today's Progress : Finished the twenty fifth lecture K-MEANS CLUSTERING in the Bloomberg Machine Learning Course.
Today's Progress : Did a project on BigMart sales prediction. I used Linear Regression to predict the sales. And learned about data imputation. I took the project from this link
Link of Work: Commit
Today's Progress : Did a project on twitter sentiment analysis. Learned how to process the strigs inside the dataset. Got the project from here but didn't use the same dataset. But I could't complete the entire analysis. So I will do it again tomorrow.
Link of Work: Commit
Today's Progress : Tried to do twitter sentiment analysis again but couldn't complete due to some unkonown errors. Here is the link to the failed work.
Link of Work: Commit
Today's Progress : Learned how to deal with time series. Tried to do a project on air passengers prediction using ARIMA. But couldn't complete. I will continue with the same tomorrow. I got the project from this link and tried to learn the process.
Link of work : Commit
I also created a jupiter notebook template which tells you what are the steps to be done during a text analysis. Here's the link
Today's Progress : Completed the time series analysis using ARIMA model.
Link of Work : Commit
Today's Progress : Finished the twenty sixth lecture GAUSSIAN MIXTURE MODELS in the Bloomberg Machine Learning Course.
Today's Progress : Tried to do iris flower classification using keras but failed. And finished the twenty seventh lecture EM ALGORITHM FOR LATENT VARIABLE MODELS in the Bloomberg Machine Learning Course.
Link of Work : Commit
Today's Progress : Finished the twenty eigth lecture NEURAL NETWORKS in the Bloomberg Machine Learning Course. And learned how to download stock market data using nsepy and did some basic EDA. Couldn't do much :(
Link of Work : Commit
Today's Progress : Finished the twenty ninth lecture BACK PROPAGATION AND CHAIN RULE in the Bloomberg Machine Learning Course.
Today's Progress : Finished the last lecture NEXT STEPS in the Bloomberg Machine Learning Course.
Today's Progress : Finished reading the second chapter in the book Hands on Machine Learning with Scikit Learn and Tensorflow and implemented the code.
Today's Progress : Started a new course on Neural Networks and Deep Learning in Deep Learning Specialization at Coursera and finished the introduction part.
Today's Progress : Watched the lectures in the Neural Networks and Deep Learning course.
Today's Progress : Watched the lectures in the Neural Networks and Deep Learning course.
Today's Progress : Watched the lectures in the Neural Networks and Deep Learning course.
Today's Progress : Watched the lectures in the Neural Networks and Deep Learning course and finished the second week of the program.
Today's Progress : Tried to do House Price Prediction but the dataset was too big so I couldn't even do a perfect EDA.
Link of Work : Commit
Today's Progress : Completed the second weeek's assignment in the Neural Networks and Deep Learning course.
Today's Progress : Learned about different time series forecasting models. And tests for checking the stationarity of a time series.
Link of Work : commit
Today's Progress : Tried to predict shampoo sales using ARIMA. I wasn't successfull but still learned a lot.
Link of Work : Commit
Today's progress : Learned about Auto ARIMA.
Link of Work :
Today's Progress : Learned some basics about keras model and created a simple neural network.
Link of Work : Commit
Today's Progress : Started a machine learning course in coursera. Learned in-depth about Linear Regression algorithm, cost function and gradient descent.
Today's Progress : Learned Convolutional Neural Network and implemented it using Keras on MNIST dataset.
Link of Work : Commit
Today's Progress : Started reading the book Deep Learning with Keras by Antonio Gulli and Sujit Pal and finished the first chapter.
Today's Progress : Started the third week in the Neural Networks and Deep Learning course called the Shallow Neural Network. Watched some lectures.
Today's Progress : Watched some videos in the Neural Networks and Deep Learning course and wrote a function to implement a simple gradient descent.
Link of Work : Commit
Today's Progress : Completed all videos in the third week of Neural Networks and Deep Learning course.
Today's Progress : Completed the assignment in the third week of the Neural Networks and Deep Learning course. In the assignment I learned to build a neural network from scratch.
Today's Progress : Started the fourth week in the Neural Networks and Deep Learning Course.
Today's Progress : Learned some basics about tensorflow architectue and how to create a neural network using tensorflow.
Today's Progress : Watched some videos in the Neural Networks and Deep Learning course and go some insights about implementing a deep neural network.
Today's Progress : Completed the fourth week lectures in the Neural Networks and Deep Learning course and tried to do the week's assignment but couldn't finish it.
Today's Progress : Finished the fourth week's assignment in the Neural Networks and Deep Learning course and also created a simple perceptron.
Link of Work : Commit
Today's Progress : Learned how to use keras with tensorflow. Created a simple digit classifier using tensorflow.keras module.
Link of Work : Commit
Today's Progress : Found a project on Medium. Downloaded the csv and began the project. Finished some rudimentary steps.
Link of Work : Commit
Today's Progress : Started reading the book Learning Tensorflow to understand and learn the basics of tensorflow. Finished the first two chapters.
Today's Progress : Completed the third chapter in the book Learning Tensorflow. Created a graph to to do linear regression using tensorflow.
Link of Work : Commit
Today's Progress : Created a support Vector Machine from scratch.
Link of Work : commit
Today's Progress : Created a graph in tensorflow to compute logistic regression.
Link of Progress : Commit
Today's Progress : Started the next course Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization in the Deep learning Specialization and watched some intro videos.
Today's Progress : Watched some videos in the first week of the course Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization.
Today's Progress : Finished all videos in the first week of the course Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization.
Today's Progress : Completed the first week assignment in the course Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization.
Today's Progress : Watched some videos in the second week of the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Watched some videos in the second week of the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Completed all videos in the second week of the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Finished the second chapter in the book Hands on Machine Learning using Tensorflow andd Scikit-Learn and implemented the codes.
Today's Progress : Completed the second week assignment in the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Learned some basics about Reinforcement Learning from watching Youtube videos.
Today's Progress : Revised all basic functionalities and applications of the Pandas library.
Today's Progress : Revised all the fundamental features of the library Matplotlib.
Today's Progress : Revised all the basic machine learning algorithms and implementation codes.
Today's Progress : Worked a little on the Fynd image classifier project. Didn't put in much work.
Today's Progress : Started the third week video series in the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Watched some videos in the third week of the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Completed watching all the videos in the third week of the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Completed the third week assignment in the course Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
Today's Progress : Learned the basics of recommendation algorithms but couldn't implement them :(
Today's Progress : Learned the basics of Natural Language Processing(NLP) and implemented the concepts to identify spooky authors from a kaggle dataset.
Link of Work : Commit
Today's Progress : Learned Extreme Gradient Boost(XGBoost) algorithm and implemented it to predict if a whether or not a patient has diabetes. I used XGBClassifier and got an accuracy of 79%. Didn't dive deep to increase the accuracy :(
Link of Work : Commit
Today's Progress : Completed the Cats vs Dogs Kaggle Competition using VGG-16 convolutional neural network.
Link of Work : Commit