Israel Chaparro

[Israel Chaparro @IsraelChaparroC]

@agustinms67 Alonso es mufa. Lo pones en mercedes para la siguiente carrera y llega 7 como siempre.

[Israel Chaparro @IsraelChaparroC]

@Limalimon2021P @teleticketperu No es

[Israel Chaparro @IsraelChaparroC]

Flores Hnos Dorado VIP parte inferior. No quiero imaginarme como son los otros servicios. Ruta AQP-Tacna.

[Israel Chaparro @IsraelChaparroC]

@ale_ames Y la cifra negra?

[Israel Chaparro @IsraelChaparroC]

Overleaf is down :(
Isn't just me

[Israel Chaparro @IsraelChaparroC]

@aderly Encuentro
Problemas para subir
Se queda dentro
Mi primera chamba…

[Israel Chaparro @IsraelChaparroC]

@mariajruizg1 Si te revientan la luna del coche para robar. Dirás que fue porque no le pusiste láminas de seguridad de 12mm?

[Israel Chaparro @IsraelChaparroC]

@__pedram @neuromatch Hi Pedram, I fully support what you mention. I accepted the role thinking that the pay was the same for every TA. But a pay differentiated by country is a negative discrimination that perpetuates inequalities and negative stereotypes. As well as demoralizing the lower paid TA's..

[Israel Chaparro @IsraelChaparroC]

@interbank @CarliChan Hola @interbank, ¿Cuándo regresará el retiro de fondos vía IBK?

[Israel Chaparro @IsraelChaparroC]

@ragna1x The dog ran very fast

[Israel Chaparro @IsraelChaparroC]

@DaniiQuilodran También me va mal

[Bojan Tunguz @tunguz]

“A young man, ginger hair, sings a song in front of various urban backgrounds, 80s hairstyle and outfit, wild dancing gyrations, background dancers, 80s video resolution, photorealistic, pop video.”

[Bindu Reddy @bindureddy]

Time-series forecasting - AI to predict the future

While LLMs and Gen AI have received a lot of attention, state-of-the-art (SOTA) time-series forecasting models almost seem magical when they can predict a future value with high accuracy. They are used to predict stock prices, weather, retail demand, economic indicators like inflation, interest rates, and even climate change.

Until recently statistical algorithms that work by analyzing historical data to detect patterns, trends, and relationships in the data were the standard way to do time-series forecasting.

The two most popular statistical methods are
ARIMA (AutoRegressive Integrated Moving Average): Combines autoregressive (AR), differencing (I), and moving average (MA) methods to model time-series data, capturing trends and seasonal patterns.

Exponential Smoothing: Utilizes weighted averages of past observations, with the weights decaying exponentially as the observations get older, to predict future values.

Recently, however, several deep learning algorithms, have outperformed statistical and classical machine learning methods. Here are the key steps involved in creating an applied AI system in forecasting.

Data Preprocessing: This data may need to be cleaned and transformed into a suitable format, such as normalizing or scaling the values.

Building the Neural Network: Different NN architectures are applicable to different problems.

LSTMs, an RNN can learn and remember long sequences.
widely used in forecasting where long-term dependencies exist. This might include stock price prediction, weather forecasting, etc.

CNNs utilize convolutional layers that can detect local patterns or features and can be applied to time series forecasting to recognize spatial patterns in sequences.

Current SOTA architectures tend to be Transformer architectures. They can capture long-range dependencies in data by using self-attention. They can also be used for time series forecasting by encoding the past values of the time series into a sequence of vectors and then decoding the vectors to produce the predicted future values.

Hyperparameter Tuning: Tuning and optimizing parameters like learning rate, number of layers, and the type of loss function that may apply can at times significantly improve model performance. Deep learning models come with many "knobs" you can turn to optimize performance, such as learning rate, number of layers, and number of neurons in each layer. Finding the right combination is essential but often tricky, and it may require experimentation.

Model Evaluation: Once your models are trained, you evaluate them by measuring how well they predict future values they haven't been trained on. Training multiple models using a variety of algorithms and picking the best model is recommended

Metrics like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE) are popular metrics that are used to quantify the difference between the predicted and actual values.

Deployment and Maintenance: Finally, the model may be integrated into a broader system to make ongoing predictions. Regular monitoring of drift, retraining, and updating is necessary, as changes in underlying patterns may cause the model's performance to degrade over time.

An end-to-end MLOps system can be used to set up pipelines, train and evaluate models and maintain them over time. We over at https://t.co/dJ2B4Jig2U have invented several DL techniques and provide a SOTA platform to create and deploy models.

[Israel Chaparro @IsraelChaparroC]

@jillian_ruz Con roaming?

[Israel Chaparro @IsraelChaparroC]

@MovistarPeru espero que regresen los canales H y H2 pronto o tendré que cambiar de operador.

[Israel Chaparro @IsraelChaparroC]

@AmazonHelp I explain when I start the chat that the problem I have is that they always tell me that the zip code is wrong, and they keep asking me for the zip code 1 hour later, they don't solve my problem at all.

[Israel Chaparro @IsraelChaparroC]

@AmazonHelp They repeat over and over again that my zip code is wrong, when it's not, I see on https://t.co/dutsDt0elt that it's the correct one. Then they say they will call me, but they don't call me, then they tell me to call them, when I can't call the U.S. from here.

[Israel Chaparro @IsraelChaparroC]

@AmazonHelp I've been trying to solve this for 4 hours by chat, your answer doesn't help me.

[Israel Chaparro @IsraelChaparroC]

@AmazonHelp .com, and Amazon Prime Video. I'm from Perú. Why I say that my account has been reseted? Prime Video suscription, profiles, wishlist, history of buys, history of searchs, etc no longer exist.